The Data Download

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What does it take to lead data strategy at a Fortune 500 company for over a decade—through industry shifts, technological revolutions, and the dawn of generative AI? In this kickoff episode of Season 4, host Thomas Brence sits down with Justin Heller, Chief Data Officer at Synchrony, to explore how a foundation in political science, interactive telecommunications, and process thinking has shaped his enduring career in data leadership.Justin shares the strategic mindset that's guided his team's efforts across technology, people, and process, and how his background in game theory informs his value-focused approach to data. From navigating the ethical complexities of AI to measuring data's contribution to enterprise risk reduction, Justin offers an honest, insightful look at the evolution—and future—of the CDO role.Three reasons you should listen to this episode:1. Redefine data leadership through interdisciplinary thinking. Learn how Justin Heller's unique academic and professional background shapes his approach to data strategy—and how connecting people, process, and technology drives long-term impact.2. Bridge AI adoption and governance with practical ethics. Discover why a “human in the loop” model isn't enough on its own, and how organizations can better prepare their workforce for responsible AI use.3. Tie data quality to business value, not bureaucracy. Hear how Synchrony balances agility with risk management, turning governance into an enabler instead of a roadblock—and why relevance of information (ROI) may matter more than return on investment.ResourcesConnect with ThomasConnect with JustinEnjoyed this Episode?Be sure to follow us so you never miss an update. You can leave us a review on Apple or Spotify, and share it with your friends and colleagues to help others learn more about the importance of a data-first digital transformation approach.Have questions? You can connect with us on LinkedIn. For more updates, please visit our website.

The team is taking a quick break but we'll be back in 2025 with even more insights, stories, and inspiration from data leaders around the world.In the meantime, catch up on any episodes you may have missed, and don't forget to follow the show so you'll be the first to know when we're back. We'll see you in 2025!

Empowering teams with data is essential for any organization aiming to drive better decision-making. This week, Chief Data Citizen, Stijn Christiaens connects with Ruben Missinne, Data Analytics Officer at Colruyt Group, to break down how the company built a “data marketplace” to support decentralized access, enabling employees across departments to leverage data effectively and independently.Whether fostering data craftsmanship and trust through hands-on learning opportunities like hackathons and collaborative coaching, or by decentralizing data access and prioritizing transparency, Colruyt has built a culture where data is trusted and actionable. Leaders looking to transform their own data strategy will find valuable insights in their approach to making data an integral part of daily operations.Three reasons you should listen to this episode:1. Empower teams through decentralized data access. Discover how Colruyt's “data marketplace” model enables employees across the organization to use data independently, driving more effective, data-informed decision-making.2. Strengthen data culture with practical, hands-on learning. Ruben shares Colruyt's approach to data literacy through hackathons and collaborative coaching, making data skills accessible to everyone.3. How transparency and trust enhance data use. Explore how Colruyt builds trust in its data through transparency and open access, ensuring that data is both reliable and integral to daily operations.ResourcesConnect with StijnConnect with RubenEnjoyed this Episode?Be sure to follow us so you never miss an update. You can leave us a review on Apple or Spotify, and share it with your friends and colleagues to help others learn more about the importance of a data-first digital transformation approach.Have questions? You can connect with us on LinkedIn. For more updates, please visit our website.

How are law firms embracing the power of data while navigating the unique challenges that set them apart from other industries? Jordan Galvin, the first data governance manager at Perkins Coie, reveals how legal organizations can transform their approach to data, tackling compliance, privacy, and risk management in a traditionally non-technical environment.From improving data quality to bridging the gap between legal expertise and data-driven decision-making, Jordan shares practical strategies that bring data governance to life. She also highlights the importance of fostering collaboration across departments to build a more data-driven culture. This conversation offers valuable insights for leaders looking to elevate their data governance practices within the legal landscape.Three reasons you should listen to this episode:1. How law firms harness the power of data. Discover how the legal industry is adapting to data governance, tackling challenges like compliance, privacy, and risk management while staying ahead in a rapidly evolving field.2. Practical strategies for bridging gaps. Actionable insights on improving collaboration between traditionally separate legal and data departments to create a more data-driven culture.3. Non-technical industries embracing data governance. Valuable lessons on how organizations with little technical background, like law firms, can implement effective data governance practices and turn data into a strategic asset.ResourcesConnect with ThomasConnect with JordanEnjoyed this Episode?Be sure to follow us so you never miss an update. You can leave us a review on Apple or Spotify, and share it with your friends and colleagues to help others learn more about the importance of a data-first digital transformation approach.Have questions? You can connect with us on LinkedIn. For more updates, please visit our website.

A shared understanding of data across teams might be one of the most critical tools for driving better business outcomes. Just ask Nicola Askham, the Data Governance Coach, who's full of practical advice on creating clarity around data definitions, improving collaboration and making data sharing more reliable within organizations.Miscommunication and inconsistent data definitions can easily lead to inefficiencies and mistakes. Nicola shares practical strategies for using data glossaries and catalogs to align teams, ensuring everyone is on the same page and working with accurate, trusted information. This conversation offers actionable insights for data governance leaders looking to enhance data culture and governance practices through a unified language.Three reasons you should listen to this episode:1. Create clarity around your data. Learn how establishing a common language through data glossaries and catalogs can reduce miscommunication and ensure your teams work with accurate, consistent data.2. Boost collaboration across departments. Discover practical ways to improve data sharing and alignment between teams, leading to better decision-making and fewer errors.3. Strengthen your data governance strategy. Gain insights into how a shared understanding of data can enhance your organization's data culture and governance practices, making data more reliable and easier to manage.ResourcesConnect with ThomasConnect with NicolaEnjoyed this Episode?Be sure to follow us so you never miss an update. You can leave us a review on Apple or Spotify, and share it with your friends and colleagues to help others learn more about the importance of a data-first digital transformation approach.Have questions? You can connect with us on LinkedIn. For more updates, please visit our website.

Faced with the complexity of managing massive amounts of digital data, it's no surprise that organizations are rethinking how to empower their teams. Garth Gehlbach, Head of Data Governance at Western Governors University, joins us live at DC 24 in Orlando to reveal how the university implemented a self-service data discovery platform, transforming the way users access and leverage information.By leveraging a "Google for data" approach, WGU has built a system that allows users to quickly find and confidently trust the data they need. And thanks to the power of metadata in providing critical context and making data more accessible and reliable, WGU's self-service model not only offers a practical blueprint for overcoming fragmented data sources and inconsistent reporting; it also paves the way for a more scalable and efficient data governance model.Three reasons you should listen to this episode:1. Empowering your team with self-service data tools. Discover how implementing a self-service data discovery platform can transform your organization's efficiency, enabling users to independently find, understand, and trust data.2. Unlocking the power of metadata. Hear how WGU used metadata to provide critical context, making data more accessible and reliable, and how you can apply similar strategies to your data governance efforts.3. Overcoming data governance challenges. Gain insights into tackling common issues like fragmented data sources, inconsistent reporting, and building trust in your data through proactive governance strategies.ResourcesConnect with ThomasConnect with GarthEnjoyed this Episode?Be sure to follow us so you never miss an update. You can leave us a review on Apple or Spotify, and share it with your friends and colleagues to help others learn more about the importance of a data-first digital transformation approach.Have questions? You can connect with us on LinkedIn. For more updates, please visit our website.

Metadata isn't just a buzzword; it's the foundation for driving business value and fostering a data-driven culture. Tanja Glisin, Data Governance Office Manager at TELUS, joins Collibra's Keren Corely, Director of Go-to-Market Digital Programs, on location at DC 24 in Orlando, to discuss the transformative power of metadata management.Now five years strong, TELUS's metadata management program is designed to empower the organization by enabling business units to efficiently manage, govern and leverage data assets. Tanja shares insights into the program's mission to democratize data, the importance of stakeholder management and the role of continuous improvement in maintaining program success. She also emphasizes the significance of building a metadata repository to achieve critical mass and the strategic use of metadata to create valuable data products that drive innovation and efficiency across the organization.Three reasons you should listen to this episode:1. Empowering Data Democratization. Hear how transforming data (by making it accessible and usable across the organization) can break down silos and foster a data-driven culture.2. Strategic Metadata Management. Gain valuable insights into TELUS's approach to building and managing a comprehensive metadata repository, enabling efficient data governance and the creation of high-value data products.3. Continuous Improvement and Stakeholder Management. Learn about the importance of continuous improvement, stakeholder engagement, and risk management in driving the success of a metadata management program and how these practices can be applied to your own data initiatives.ResourcesConnect with KerenConnect with TanjaEnjoyed this Episode?Be sure to follow us so you never miss an update. You can leave us a review on Apple or Spotify, and share it with your friends and colleagues to help others learn more about the importance of a data-first digital transformation approach.Have questions? You can connect with us on LinkedIn. For more updates, please visit our website.

Show Notes

Over the past two decades, data has become critical to nearly every industry. In the realm of healthcare, it's a game-changer. Anthony Macaione, Data Governance Manager, and Craig Hunter, Solutions Analyst, reveal how MemorialCare's cutting-edge data governance practices are revolutionizing patient outcomes and streamlining operations.MemorialCare's mission focuses on improving the health and well-being of individuals and communities by leveraging trusted data. As Anthony and Craig shed light on the organization's data governance journey, they reveal the challenges of making data accessible and useful across the board. From the integration of data governance with business processes to the measurable success seen in increased data utilization and streamlined operations, this live DC 24 session underscores the importance of transparency, role-specific data access, and continuous improvement in healthcare data management. Three reasons you should listen to this episode:1. Transforming patient care with data. Discover how MemorialCare leverages data governance to improve patient outcomes and enhance operational efficiency in a healthcare setting.2. Real-world implementation. Gain insights into the practical steps MemorialCare took to build a comprehensive report catalog, integrating data governance with business processes to make data more accessible and useful.3. Driving operational efficiency. Learn about the importance of transparency, role-specific data access, and continuous improvement in driving the success of healthcare data management programs.ResourcesConnect with ThomasConnect with AnthonyConnect with CraigEnjoyed this Episode?Be sure to follow us so you never miss an update. You can leave us a review on Apple or Spotify, and share it with your friends and colleagues to help others learn more about the importance of a data-first digital transformation approach.Have questions? You can connect with us on LinkedIn. For more updates, please visit our website.

Data isn't just the new oil; it's the engine driving transformation. Listen as Northern Trust's Adrienne Kiessel, Head of Enterprise Data Governance and Subbaiah Maneyapanda, Senior VP of Enterprise Data Management & Analysis break down how their organization's data strategy is revolutionizing its approach to data governance and management.Of course, achieving such significant strides in data governance isn't easy. But by treating data as a valuable asset and continuously fostering a proactive, collaborative culture, Northern Trust has shifted away from siloed operations to embrace a truly cohesive strategy; one that includes the use of data management tools, like Collibra. Recorded live at DC 24 in Orlando, this session is a rare glimpse at how to empower practitioners within your organization to begin leveraging data for innovation and informed decision-making.Three reasons you should listen to this episode:1. Proactive Data Culture. Learn how Northern Trust is moving from reactive to proactive data management, breaking down silos and fostering a culture where data is treated as a core asset across the organization.2. Strategic Integration. Discover the strategic integration of data governance tools like Collibra, which enhances data quality and consistency, supporting regulatory compliance and business innovation.3. Empowering Practitioners. Understand the comprehensive approach to empowering thousands of data practitioners through education, support, and a centralized governance model, driving meaningful and actionable insights.ResourcesConnect with ThomasConnect with AdrienneConnect with SubbaiahEnjoyed this Episode?Be sure to follow us so you never miss an update. You can leave us a review on Apple or Spotify, and share it with your friends and colleagues to help others learn more about the importance of a data-first digital transformation approach.Have questions? You can connect with us on LinkedIn. For more updates, please visit our website.

How does a major player in the housing finance industry leverage data to drive business value and support its mission? Listen to find out as Chief Data Citizen, Stijn Christaens, chats with Freddie Mac's VP & Chief Data Officer, Arvind Jagannathan, and Director of Data Analytics, Vikram Chopra, to uncover the sophisticated data strategies that power the mortgage leader's operations.Freddie Mac's journey of modernizing its data ecosystem and steering clear of the data swamp highlights their innovative approach and dedication to effective data governance. As we examine their offensive and defensive strategies, we see how advanced analytics and AI help to transform operations and enhance decision-making in an incredibly regulated industry. Recorded live at DC 24 in Orlando, this deep dive into the practical applications of data is an amazing look at the intersection of data management, governance and business strategy.Three reasons you should listen to this episode:1. Modernizing Data Ecosystems. Learn how Freddie Mac transitioned from legacy systems to a modern data infrastructure, ensuring data quality and compliance while driving business value.2. Offensive and Defensive Strategies. Understand the balance between offensive and defensive data strategies, including data consumer registration and advanced analytics to support business objectives.3. AI Integration. Discover how Freddie Mac is leveraging AI to improve their data processes and decision-making, setting the stage for future innovations in the housing finance industry.ResourcesConnect with StijnConnect with JagConnect with VikramEnjoyed this Episode?Be sure to follow us so you never miss an update. You can leave us a review on Apple or Spotify, and share it with your friends and colleagues to help others learn more about the importance of a data-first digital transformation approach.Have questions? You can connect with us on LinkedIn. For more updates, please visit our website.

Show notes

What's the secret sauce behind McDonald's ability to stay ahead in the fast-food industry? John Tucker, Director of Enterprise Data Governance, unveils how McDonald's uses data to not only enhance customer experience but also streamline crew operations with cutting-edge AI applications.From personalizing customer interactions to implementing AI-driven tools that support crew efficiency, John reveals how McDonald's leverages data to maintain its competitive edge. And his many insights on the company's innovative data strategies only reinforce the role of data governance in ensuring quality and consistency across all industries. Recorded live at DC 24 in Orlando, this conversation is a must-listen for anyone interested in the practicalities of data-driven transformation in a global enterprise.Three reasons you should listen to this episode:1. Practical AI Applications. John shares how McDonald's uses AI to streamline crew tasks, such as using chatbots to provide instant answers, which enhances efficiency and reduces manual work.2. Comprehensive Data Governance. Learn about the innovative structure of McDonald's data governance team, including roles like data librarian and change adoption manager, and how this approach ensures data quality and consistency.3. Building the Plane. Discover how McDonald's Project Runway is driving data standardization and operational improvements, making data more accessible and meaningful across the organization.ResourcesConnect with ThomasConnect with JohnEnjoyed this Episode?Be sure to follow us so you never miss an update. You can leave us a review on Apple or Spotify, and share it with your friends and colleagues to help others learn more about the importance of a data-first digital transformation approach.Have questions? You can connect with us on LinkedIn. For more updates, please visit our website.

What's the point of creating value with your data if you never cash it in? This week, Barb Wixom, Principal Research Scientist at MIT Sloan's Center for IS Research, takes us through the critical but oft neglected journey of turning data into definitive financial gains.In peeling back the layers inherent to the value creation process, Barb insists that the leap from data to dollars must involve more than simply generating insights; it requires a strategic pivot towards value realization. With the IWS (Improve, Wrap, Sell) framework, we'll help demystify the process, and show you exactly how operational enhancements and product advancements can be carefully leveraged to achieve financial outcomes. It's a comprehensive look at the practicalities of converting data into tangible value; a must-listen for anyone looking to navigate the complexities of data monetization effectively.Three reasons you should listen to this episode:1. Value Creation to Realization. Barb breaks down the critical steps from value creation to value realization in data monetization, highlighting a commonly overlooked phase that is crucial for translating data benefits into financial returns.2. The IWS Framework. A simple yet powerful tool for organizations to strategize their data monetization efforts, providing a clear pathway from operational improvements to selling information-based solutions.3. Sustainability and Data Monetization. For any effort to be viable long-term, it must not only generate social or operational benefits but also secure financial returns, thereby ensuring the initiative's economic feasibility over time.ResourcesConnect with JayConnect with BarbEnjoyed this Episode?Be sure to follow us so you never miss an update. You can leave us a review on Apple or Spotify, and share it with your friends and colleagues to help others learn more about the importance of a data-first digital transformation approach.Have questions? You can connect with us on LinkedIn. For more updates, please visit our website.

Is data the Coast Guard's compass to new horizons? This week, Toan Do, Area Vice President of Federal Sales at Collibra, invites Capt. Brian Erickson, Chief Data and Artificial Intelligence Officer at the United States Coast Guard, to shed some light on the Coast Guard's transformative journey from traditional navigation to data-driven decision-making, illustrating how data is becoming the compass guiding the organization's mission and operations.Amid the challenges of implementing data analytics and AI within the Coast Guard, Capt. Erickson has come to recognize the value of starting small, focusing on high-priority use cases, and fostering a data-literate workforce. His personal transition from a career aviator to leading the Coast Guard's first data office is a perfect parallel to the evolving role of data as a strategic asset in enhancing mission effectiveness. And as if that's not already a shining example of leadership in data, Capt. Erickson is now preparing to pass on this newfound passion to his successor, setting the stage for a bright future of enthusiastically data-literate military personnel.Three reasons you should listen to this episode:Unique perspective on data's role. Capt. Erickson's journey from a career aviator to leading the Coast Guard's first data office highlights how data can be leveraged as a strategic asset in a multifaceted organization.Practical insights on data implementation. When approaching the integration of data analytics and AI, starting with small initiatives and developing a workforce that is proficient in data literacy yields big results.Strategic approach to data management. Order and efficiency are clearly a necessity in data management, as is incremental growth and easy wins to build confidence.ResourcesConnect with ToanConnect with Capt. EricksonEnjoyed this Episode?Be sure to follow us so you never miss an update. You can leave us a review on Apple or Spotify, and share it with your friends and colleagues to help others learn more about the importance of a data-first digital transformation approach.Have questions? You can connect with us on LinkedIn. For more updates, please visit our website.

We all know that every bit of an organization's data ought to be treated equal, right? Well, in a world where clean data is often the status quo, Julie Fawdington, Senior Director PMO at Hewlett Packard Enterprises, invites us to ask the question, how clean is clean enough?Drawing on her extensive experience in data transformation, Julie's take on data quality suggests the need for data quality differentiation. As she puts it, the stuff in her pet's water bowl isn't the same as what's in her water bottle. But does this idea that not all data requires the same level of cleanliness really upend conventional wisdom? Or does it simply provide a more nuanced understanding of how to efficiently manage data in today's fast-paced business environment?Three reasons you should listen to this episode:1. Redefining data standards. Discover Julie's unique approach to data quality and how it can revolutionize your data management practices.2. Empowering data stewards. Examine the role of data custodians and stewards in driving business processes and effectively managing data quality and governance.3. Leadership's role in data management. Learn practical steps for how leaders can promote data quality and management within their organizations.ResourcesConnect with Julie on LinkedInEnjoyed this Episode?Be sure to follow us so you never miss an update. You can leave us a review on Apple or Spotify, and share it with your friends and colleagues to help others learn more about the importance of a data-first digital transformation approach.Have questions? You can connect with us on LinkedIn. For more updates, please visit our website.

It's no secret that AI has seen massive success in FinTech, but what hidden forces are driving this success, and how do they transform raw data into global opportunities? This week, guest host Stijn Christiaens invites Peep Küngas, Data Architect at Monese to decode the intricacies of data quality management and its profound impact on the tech landscape, offering fresh insights into this crucial yet often overlooked backbone of AI innovation.How do the smallest details in data curation fuel major breakthroughs in AI-driven solutions? And what unseen challenges do data architects grapple with in their mission for impeccable data? Listen as Peep and Stijn peel back the layers of data quality management to reveal the critical role of precision and insight in shaping the future of FinTech and our next technological leap forward.Three reasons you should listen to this episode:1. The foundation of AI success. Understand the integral role of data quality management in enhancing AI's performance in the FinTech industry.2. Navigating data complexities. Examine the challenges, strategies, and rigorous process behind ensuring impeccable data quality.3. Data quality as a discipline. Find out what fitness routines teach us about the continuous effort and collaboration required to maintain and improve the backbone of digital innovation.ResourcesConnect with Peep on LinkedInEnjoyed this Episode?Be sure to follow us so you never miss an update. You can leave us a review on Apple or Spotify, and share it with your friends and colleagues to help others learn more about the importance of a data-first digital transformation approach.Have questions? You can connect with us on LinkedIn. For more updates, please visit our website.

In the intricate world of financial data governance, Dennis van de Graaf, VP of Data Governance at WinTrust Financial, highlights a crucial component: the definition and empowerment of data owners. His insight reveals how assigning clear ownership of data sets within an organization is fundamental to ensuring data accuracy, security, and compliance.Dennis's approach underscores the role of data owners as stewards of data quality and guardians of data access and security, particularly in the heavily regulated financial industry. His discussion not only delves into the practical aspects of establishing data owners but also into their strategic importance in aligning data usage with organizational goals. This concise exploration into the responsibilities and impact of data owners offers valuable guidance for anyone looking to enhance data governance practices in their organization.Three reasons you should listen to this episode:1. The importance of data ownership. Why defining data owners is crucial in data governance, especially in the financial sector.2. Insights into data stewardship.The responsibilities and strategic impact of data owners on data quality, security, and compliance.3. Best practices in your organization. Practical knowledge on how to effectively establish and support data owners, enhancing your organization's data governance framework.ResourcesConnect with Dennis on LinkedInEnjoyed this Episode?Be sure to follow us so you never miss an update. You can leave us a review on Apple or Spotify, and share it with your friends and colleagues to help others learn more about the importance of a data-first digital transformation approach.Have questions? You can connect with us on LinkedIn. For more updates, please visit our website.

At the intersection of data and education, transformative initiatives are shaping the future of higher education institutions. Alice Fleck, Enterprise Data Governance Manager at the University of North Carolina at Greensboro (UNCG), brings to light the critical role of data governance in academic settings.The significant impact of well-structured data governance committees, which are integral to managing extensive data landscapes, ensure that data-driven decisions enhance student outcomes and institutional performance. With a focus on metadata, classification, and organization, the methodology of integrating library and information science principles into data governance provides a fresh perspective on managing and extracting value from data assets. As the data landscape evolves, these insights underscore the importance of innovative data governance strategies in shaping the future of higher education and beyond.Three reasons you should listen to this episode:1. Data governance in academia. Learn how UNCG's innovative data governance strategies are transforming higher education.2. Enhancing student outcomes. Discover the role of data in improving student performance and graduation rates.3. Broad applications of data. Gain insights into the diverse impact of data governance across various sectors.ResourcesConnect with Alice on LinkedInEnjoyed this Episode?Be sure to follow us so you never miss an update. You can leave us a review on Apple or Spotify, and share it with your friends and colleagues to help others learn more about the importance of a data-first digital transformation approach.Have questions? You can connect with us on LinkedIn. For more updates, please visit our website.

The digital realm's new currency is data, yet its value is often as enigmatic as it is critical. Sanjeev Mohan, Principal of SanjMo and former Gartner analyst, decodes the complexities of data valuation, advocating for a product-oriented view that frames data's utility and impact within an organization. The prerequisites for defining a 'data product'—from maintaining stringent quality and availability standards via Service Level Agreements to managing its lifecycle for enduring relevance— bring into focus the role of the data product manager. This role is vital to ensuring continuous enhancement and overseeing the retirement of data products; a job that guarantees these products remain a driving force for organizational value.In the pursuit of measurable benefits, treating data with the rigor of product management emerges as a beacon for Chief Data Officers, offering concrete metrics through the creation and utilization rates of data products, and providing a clear gauge for the pace and quality of innovation in data work.Three reasons you should listen to this episode:1. Data Product Insights. Grasp the value of data work as Sanjeev Mohan breaks down the essence of data products and their role in shaping business strategies.2. Data Observability. Learn about the critical nature of data observability and quality, and why these factors are non-negotiable in the pursuit of high-caliber data standards.3. Industry Foresight. Gain perspective on the current and future trends of data analytics as seen through the lens of an industry veteran.ResourcesConnect with Sanjeev on LinkedInAnd for a deeper understanding of data products, check out Sanjeev's book, "Data Products for Dummies".Enjoyed this Episode?Be sure to follow us so you never miss an update. You can leave us a review on Apple or Spotify, and share it with your friends and colleagues to help others learn more about the importance of a data-first digital transformation approach.Have questions? You can connect with us on LinkedIn. For more updates, please visit our website.

Becoming "data driven" transcends mere technical implementations—it's an organizational culture rooted in deliberate mindsets and collaborative strategies. Nico Huybrechts, CEO at Datashift, elucidates this concept, sharing from a wellspring of expertise on fostering a data-centric culture that's embedded in an organization's DNA.While expounding on the notion of 'data-preneur tiger teams,' which hints at a daring approach to tackling challenges in the data realm, Nico's mantra, "achieve impact together," resounds as a call for deep organizational collaboration on strategy, emphasizing that there's no separate data strategy from the business strategy. This approach, enriched with deep listening skills and meaningful cross-organizational connections, not only aligns teams but embeds a data-driven ethos within the organizational fabric, paving the way for sustained success.Three reasons you should listen to this episode:1. Unlock the roadmap to becoming a data-driven entity. Nico Huybrechts shares actionable insights on blending technical and human elements to foster a data-centric culture, a crucial step for leaders aiming to leverage data for enhanced business outcomes.2. Learn practical strategies to enhance business agility. Delve into strategic alignment, the concept of data-preneur tiger teams, and the transition from creative to running mode for data projects to tackle common challenges in data strategy execution.3. Gain a holistic understanding of embedding a data-driven ethos. Explore the importance of deep listening. organizational collaboration, and meaningful cross-organizational connections to get a well-rounded perspective on truly becoming data-driven.ResourcesConnect with Nico on LinkedInEnjoyed this Episode?Be sure to follow us so you never miss an update. You can leave us a review on Apple or Spotify, and share it with your friends and colleagues to help others learn more about the importance of a data-first digital transformation approach.Have questions? You can connect with us on LinkedIn. For more updates, please visit our website.

A seismic shift is underway at Booking.com as the travel giant embarks on an ambitious cloud migration and data transformation journey. In this episode, Milo Milovanovic, Senior Director of Big Data Technologies, offers an insider's look at how they are reshaping their data analytics and machine learning platforms to accelerate innovation. By transitioning to the cloud and establishing robust data governance, Booking.com aims to unlock the full potential of their data. Milo explains how improved data quality, access controls, and lineage tracking enable analysts to spend less time prepping data and more time unlocking actionable insights. The end goal is simple: leverage technology to deliver unparalleled customer experiences… and trust in data to drive vital insights for the organization.Three reasons you should listen to this episode:1. Learn how data governance and quality unlocks innovation in the cloud. Milo provides an invaluable perspective into how Booking.com is streamlining their data analytics and machine learning platforms. By focusing on governance, access controls, and data transparency, they empower analysts to spend less time prepping data and more time generating impactful insights.2. Discover how to accelerate your analysts' productivity. Booking.com aims to reduce the time analysts spend cleansing data and increase the time they spend on value-add analysis. Milo explains how robust data governance and cloud migration helps them achieve this goal.3. Gain insider tips on executing major cloud transformations. Milo offers an insider's view of the real-world complexities involved in migrating analytics and ML platforms to the cloud. Tune in for wisdom on change management, delivering quick wins, and getting organizational buy-in.ResourcesConnect with Milo on LinkedInEnjoyed this Episode?Be sure to follow us so you never miss an update. You can leave us a review on Apple or Spotify, and share it with your friends and colleagues to help others learn more about the importance of a data-first digital transformation approach.Have questions? You can connect with us on LinkedIn. For more updates, please visit our website.Mentioned in this episode:Collibra recognized as a Leader in The Forrester Wave™Collibra was just named a leader in The 2023 Forrester Wave: Data Governance Solutions. To learn more about the report, check out http://collibra.com/datadownload-forresterwave-dgForrester Wave, Q3 2023

If the rise of Chief Data Officers (CDOs) within the public sector is any indication, we're currently witnessing a paradigm shift towards making data a fundamental cornerstone of government operations. What's more, as these agencies increasingly prioritize data, legislative acts like the Foundations of Evidence-Based Policymaking Act and the Open Data Act further underline the shift. In the quest for actionable insights from data, Adita Karkera, CDO at Deloitte Goverment, dives deep into the "so what" of data to spotlight the significance of ethically grounded AI, transparency in its applications, and the imperative for diversity in data teams. Tracing her journey from a database analyst to a pivotal, business-centric role, Adita underscores the essence of aligning data strategies with broader mission objectives. It's not just about collecting and analyzing data; it's about understanding its broader implications, the story it tells, and the impact it has on the people it serves.Three reasons you should listen to this episode:1. CDOs in the Public Sector: Understand the burgeoning role and significance of Chief Data Officers in governmental operations.2. The Universality of Data Literacy: Explore the significance of data literacy across organizations, how it's more than just for technical roles, and why CDOs are emphasizing its importance in developing a solid data culture and strategy for better outcomes.3. Ethics and Diversity in AI: Delve into the responsibilities of using AI in the public sector and the vital role of diversity, especially women, in the decision-making processes of data-driven solutions.ResourcesConnect with Adita on LinkedInEnjoyed this Episode?Be sure to follow us so you never miss an update. You can leave us a review on Apple or Spotify, and share it with your friends and colleagues to help others learn more about the importance of a data-first digital transformation approach.Have questions? You can connect with us on LinkedIn. For more updates, please visit our website.Mentioned in this episode:Collibra recognized as a Leader in The Forrester Wave™Collibra was just named a leader in The 2023 Forrester Wave: Data Governance Solutions. To learn more about the report, check out http://collibra.com/datadownload-forresterwave-dgForrester Wave, Q3 2023

Data is more than just a buzzword at Colt Technology Services; it's the linchpin of their operational evolution. In this episode, we talk with Ram Narasimhan and Rohan Pawar about how Colt is reshaping its organizational culture around a five-pillar program designed to democratize data and foster trust at every level of the enterprise.Navigating through the complexities of data quality and cloud-based governance, our guests offer invaluable insights into the convergence of business strategy and technology. They also discuss the real-world benefits of a data-driven approach, from enhancing customer experience to unlocking new revenue streams. Tune in to learn how their journey can serve as a roadmap for your own organization's data-driven transformation.Three reasons you should listen to this episode:1. Democratization in Action: Get an insider's view of Colt's five-pillar program that is setting new standards in democratizing data and fostering organizational trust.2. The Business-Technology Synergy: Understand the nuances of aligning business strategies with data and technology, as explained by experts in the field.3. Tangible Benefits: Hear firsthand about the measurable improvements in customer experience and revenue generation that a data-driven culture can achieve.ResourcesConnect with Ram on LinkedInConnect with Rohan on LinkedInEnjoyed this Episode?Be sure to follow us so you never miss an update. You can leave us a review on Apple or Spotify, and share it with your friends and colleagues to help others learn more about the importance of a data-first digital transformation approach.Have questions? You can connect with us on LinkedIn. For more updates, please visit our website.

In healthcare, data governance stands as a pivotal factor in improving both patient outcomes and operational efficiency. In this episode, Roy Schmidt, Data Governance Program Manager at Envision Healthcare, joins us to share an insider's perspective on how his organization has successfully implemented a robust data governance program, impacting both clinicians and patients alike. Roy delves into Envision Healthcare's transition toward value-based care, a model which rewards healthcare providers based on patient outcomes rather than services provided. Join us as we explore how combining effective data governance with a human-centric approach can make a transformative difference in healthcare delivery, patient satisfaction, and overall organizational goals.Three reasons you should listen to this episode:1. Real-World Success Insights: Gain a deeper understanding of Envision Healthcare's successful data governance model that optimizes healthcare delivery and patient outcomes.2. Value-Based Care Unveiled: Discover the critical role data governance plays in enabling a value-based care system, enhancing both patient satisfaction and cost-effectiveness.3. Human-Centric Data Governance: Learn how a people-first approach in data governance not only increases operational efficiency but also contributes to compassionate healthcare delivery systems.ResourcesConnect with Roy on LinkedInEnjoyed this Episode?Be sure to follow us so you never miss an update. You can leave us a review on Apple or Spotify, and share it with your friends and colleagues to help others learn more about the importance of a data-first digital transformation approach.Have questions? You can connect with us on LinkedIn. For more updates, please visit our website.

Navigating the intricacies of building a data governance program within a banking context is no small feat, requiring strategic vision, stakeholder buy-in, and detailed execution. In this episode, Börge Hansen, Strategic Data Manager at Union Investment, invites us into his world of establishing a data governance program across the organization. , where hHe reveals the nuances of his comprehensive approach and shares lessons learned along the way.Hansen emphasizes the importance of having a structured and comprehensive overview of data within a bank, a foundation that has proven critical in his role. He candidly discusses the indispensable need for designated data owners for each system and outlines the strategies he employed to secure essential stakeholder buy-in. Join us for a deep dive into Börge's journey, offering a masterclass in the tangible steps and strategic thinking required to produce exemplary results in data governance.Three reasons you should listen to this episode:Gain firsthand insights from Börge Hansen, as he navigates the complexities and challenges of building a robust data governance program in a banking environment.Understand the pivotal role of having a comprehensive and structured overview of data, and appreciate the value of designated data owners within a banking system.Learn actionable strategies for securing essential stakeholder buy-in for data governance initiatives, drawn from Börge's wealth of experience and proven track record.ResourcesConnect with Börge on PolyworkEnjoyed this Episode?Be sure to follow us so you never miss an update. You can leave us a review on Apple or Spotify, and share it with your friends and colleagues to help others learn more about the importance of a data-first digital transformation approach.Have questions? You can connect with us on LinkedIn. For more updates, please visit our website.

In part two of our enlightening dialogue with Michele Goetz, Forrester's VP and Principal Analyst, we get deeper into generative AI, underscoring the need for transparency, diligent footnoting, and strong AI governance, where critical frameworks like GRC, data security, and the role of legal teams in AI deployment take center stage.Facing the potential impact of AI on careers, the conversation unveils both the opportunities and threats that this disruptive technology can bring, further highlighting the irreplaceable value of human creativity and critical thinking… assets that machines cannot replicate. With cornerstones like product safety and ethics at the forefront, we imagine a future where AI is unequivocally a force for good.Note to listeners: Generative AI is a rapidly developing field, with numerous nuances, opportunities, and risks yet to be fully explored, such as the usage of intellectual property for source data. We look forward to continuing this exploration into the many facets of this exciting subject over time.Three reasons you should listen to this episode:Discover the intricate details of generative AI, emphasizing the importance of transparency and accuracy in creating reliable results.Assess AI's influence on careers, its potential benefits and drawbacks, and the role of human creativity and critical thinking in an increasingly automated world.Acquire a thorough understanding of AI governance, its pivotal role in guaranteeing ethical use, accuracy, and the early involvement of legal teams in AI projects.ResourcesConnect with Michele on LinkedinEnjoyed this Episode?Be sure to follow us so you never miss an update. You can leave us a review on Apple or Spotify, and share it with your friends and colleagues to help others learn more about the importance of a data-first digital transformation approach.Have questions? You can connect with us on LinkedIn. For more updates, please visit our website.

Artificial Intelligence continues to reshape our world and is evolving as we speak to become even more accessible to non-technical individuals. In this episode, Michele Goetz, Vice President and Principal Analyst at Forrester, shares some fascinating insights into AI's transformative role across various industries, including marketing and social media. In addition to exploring the emergent trend of data democratization, we delve deep into the complexities of generative AI: its training, output, and the critical competencies required for its observation and interpretation. Join us for an eye-opening exploration into this emerging realm that promises to transform the way we work and make decisions.Note to listeners : Generative AI is a rapidly developing field, with numerous nuances, opportunities, and risks yet to be fully explored, such as the usage of intellectual property for source data. We look forward to continuing this exploration into the many facets of this exciting subject over time.Three reasons you should listen to this episode:Gain an in-depth understanding of AI's evolution and how it's becoming more user-friendly for non-technical individuals, which will help you better leverage it in various fields.Explore the rising trend of data democratization and its benefits, providing you with insights into how data access can quicken decision-making and offer time to value.Understand the implications of AI democratization and the importance of AI governance and risk mitigation in strategic decision making and growth.ResourcesConnect with Michele on LinkedinEnjoyed this Episode?Be sure to follow us so you never miss an update. You can leave us a review on Apple or Spotify, and share it with your friends and colleagues to help others learn more about the importance of a data-first digital transformation approach.Have questions? You can connect with us on LinkedIn. For more updates, please visit our website.

Amid a sea of change, the retail landscape has dramatically shifted over the past five years. In this episode, Henry Rice from Frasers Group joins Chief Data Citizen, Stijn Christiaens, at Data Citizens On the Road where they explore the far-reaching impacts of Brexit, the global pandemic, and the cost of living crisis on the retail industry. In the latter part of the conversation, Henry and Stijn tackle the challenge of morphing a 'data village' into a formidable 'data metropolis.' They also explore how we can shatter the age-old boundaries between technical and business facets to become indispensable data partners to our business.Three reasons you should listen to this episode:Learn about the profound impact of Brexit, the global pandemic, and the cost of living crisis on the retail landscape, and how Frasers Group managed to adapt and thrive.Understand the pivotal role of data governance in adopting emerging technologies like generative AI and machine learning.Discover insights on transitioning from a 'data village to a 'data metropolis', the importance of aligning with the business, and how to become an indispensable data partner to your business.ResourcesConnect with Henry on LinkedinConnect with Stijn on LinkedinEnjoyed this Episode?Be sure to follow us so you never miss an update. You can leave us a review on Apple or Spotify, and share it with your friends and colleagues to help others learn more about the importance of a data-first digital transformation approach.Have questions? You can connect with us on LinkedIn. For more updates, please visit our website.

In this episode, Katie Reynolds, Director of Data Management, Analytics, and Visualization at Case Western Reserve University draws on her experience with building a data community across various universities to underscore the importance of data governance amidst extensive regulatory requirements.As we explore the rapid evolution of technology and AI, and the pivotal role of data governance communities in expediting the journey towards effective data governance in higher education, Katie's journey highlights the power of shared experiences, from success stories to challenges, and the insights gleaned from interacting with other universities. Three reasons you should listen to this episode:Grasp the complex dynamics and importance of establishing a data community in higher education, and the integral role of data governance in this context.Learn about the transformative power of data governance communities in propelling the journey towards effective data governance in higher education.Gain insights into the rapid advancements in technology and AI and their implications for the future of data governance.ResourcesConnect with Katie on LinkedinEnjoyed this Episode?Be sure to follow us so you never miss an update. You can leave us a review on Apple or Spotify, and share it with your friends and colleagues to help others learn more about the importance of a data-first digital transformation approach.Have questions? You can connect with us on LinkedIn. For more updates, please visit our website.

The significance of data literacy in our efforts to promote collaboration and decision-making cannot be overstated. In this episode, John Yelle, Executive Director for Enterprise Data Management at DTCC, takes us inside the fascinating world of the financial industry to explore the three V's of data - volume, velocity, and variety - and learn how they play a vital role in driving this digital evolution. Join us as we delve into DTCC's data management program, a seven-year journey of dedication and innovation. John shares invaluable insights about the importance of data quality, governance, and the necessary cultural changes for achieving a successful transformation. We also discuss the tangible measures of success, such as risk reduction, faster results, and effective capacity planning, which serve as proof of the merit of a data-first digital transformation approach.Three reasons you should listen to this episode:Gain insights into the role of data - volume, velocity, and variety - in driving digital transformation in the financial industry.Learn about the importance of data quality, governance, and cultural changes in achieving a successful digital transformation.Understand the measures of success for a data-first digital transformation approach, including risk reduction, faster results, and capacity planning.ResourcesConnect with John on LinkedinEnjoyed this Episode?Be sure to follow us so you never miss an update. You can leave us a review on Apple or Spotify, and share it with your friends and colleagues to help others learn more about the importance of a data-first digital transformation approach.Have questions? You can connect with us on LinkedIn. For more updates and additional resources, please visit our website.

Discover the fascinating world of data marketplaces and unlock the potential of monetizing your organization's data in our conversation with Jay Bhankharia, a Senior Director at Databricks. Jay shares his expertise on how data marketplaces connect buyers and sellers of data assets and discusses the role of Language Learning Models (LLMs) in enhancing the user experience and aiding data providers in sharing and selling data more effectively.In this episode, we'll explore the increasing importance of data marketplaces for businesses in the digital age, highlighting a Gartner study that states that companies who collaborate and share data have three times better economic outcomes than those that don't. Learn how data marketplaces offer an open platform for customers to access data from multiple vendors, transferring it into their own tools and platforms with ease. We also touch on the impact of controls in data marketplaces to ensure data products are user-friendly and easy to purchase, and the exciting advancements in technology that have enabled companies to access and use data more efficiently, such as cloud computing, data science, and governance and access controls. Don't miss our conversation on the future of data marketplaces and how they're becoming a key component of business success.ResourcesConnect with Jay on LinkedinEnjoyed this Episode?If you did, subscribe and share it with your friends! Post a review and share it! If you enjoyed tuning in, then leave us a review. Have any questions? You can connect with us on LinkedIn. For more updates, please visit our website.

Can data governance programs evolve to provide even greater value from our data? That's the question we tackle with our insightful guest, Raluca Alexandru, an analyst at Forrester. We talk about the key components of a data governance program, such as people, process, and technology, as well as the critical role that data catalogs and business glossaries play in mapping out data assets, structuring them in an easily digestible way, and connecting them to business goals and objectives. The episode also delves into the need to create connected intelligence by combining data governance with AI governance programs. We discuss the potential risks of generative AI and how existing data governance frameworks can help manage those risks while creating value. We also take a closer look at the ethical and legal implications of AI programs and why AI governance is essential in reducing bias and adhering to policies and regulations. Moreover, we explore the importance of setting measurable metrics to assess the success of data governance programs, and how an intelligent federated approach can maximize their value. Don't miss this thought-provoking conversation with Raluca Alexandru that covers the future of data governance and intelligence solutions!ResourcesConnect with Raluca on LinkedinEnjoyed this Episode?If you did, subscribe and share it with your friends! Post a review and share it! If you enjoyed tuning in, then leave us a review. Have any questions? You can connect with us on LinkedIn. For more updates, please visit our website.

Data strategy in 2023 is no longer a mystery. As businesses embrace data monetization, it's vital to understand how to convert data products into revenue sources. In this episode, we chat with Stijn Christiaens, co-founder and Chief Data Citizen of Collibra, who unveils the secrets of data strategy and bridges the gap between data and business language.Join us as we explore the evolving role of data engineers and their need for a deeper understanding of the products and applications they work on. We also discuss the significance of data democratization and the emerging data marketplace, which allows organizations to access and measure data value in a democratic way.Tune in to this insightful episode to stay ahead of the curve in data strategy.Here are three reasons why you should listen to this episode:1. Learn the importance of data monetization in your overall data strategy.2. Discover how the role of data engineers is evolving as they adapt to operationalizing machine learning models.3. Understand the impact of data democratization and the rise of data marketplaces on the business landscape.ResourcesConnect with Stijn on LinkedinEnjoyed this Episode?If you did, subscribe and share it with your friends! Post a review and share it! If you enjoyed tuning in, then leave us a review. Have any questions? You can connect with us on LinkedIn. For more updates, please visit our website.

Join us LIVE at Collibra's DC'22, where we talk about the relevance of data intelligence. We are joined by the 2022 Collibra Excellence Award-Winners: Acceleration All-Star winner Heather Wentworth, chief data officer of Accelerant Holdings; Program of Year winner David Mitchell, senior director of engineering of Cox Automotive; and Collibra Ranger of the Year Peter Vennel, enterprise data strategy and execution executive of Equifax.How do businesses strike the ideal balance between powerful analytics and ease of use? Tune in to learn how data intelligence can help you solve problems and grow your business.Here are three reasons why you should listen to this episode:Learn why these individuals and companies stand above the rest in data intelligence.Discover the secret to maximizing Collibra.Unravel the future of data intelligence.Resources Learn more about CollibraAccelerant Cox AutomotiveEquifaxConnect with our guestsHeather: LinkedInDavid: LinkedInPeter: LinkedIn | TwitterEpisode Highlights[01:54] Collibra Award's SignificanceAccording to Heather, the Acceleration All-Star of the Year award represents the company's efficient planning and implementation from start to production.David sees the Data Program of the Year award as a culmination of their data strategy and execution efforts. It also highlights their culture of innovation and collaboration. Winning the Collibra Ranger of the Year award, Peter considers their company's decision to use Collibra a wise investment. [06:47] How They Started in the Field of Data David was a software engineer before moving into the financial data industry, where he discovered his love for problem-solving and helping customers.Heather shifted careers because of the culture of valuing sizzle over data.Given his professional background, Peter's transition into the data industry was not by chance. As he continues to work in the field, he hopes to improve its quality.[13:12] Reduce the Swivel Chair Instead of focusing on various aspects, it is best to concentrate on system engagement.David: “As you look at bringing people processing technology together, you've got to win the hearts and minds of people to actually get involved in [system engagement].”Learn how to use Collibra's automation to pull information rather than having people do it.[14:25] The Secret Sauce Your team is the key to success.Start-ups have a significant advantage in moving around the data ecosystem quickly.Understand your company culture.Heather: “​​All of my...

Join us LIVE at Collibra's DC'22, where we talk about the importance of data governance with Joe Wallace, senior manager for Digital Asset Governance, Adobe, and Ryan Galloway, senior vice president for Moody's Corporation. How can companies improve their data quality and decision-making processes? Listen as they explore some of the challenges associated with data governance and share tips for overcoming them. Tune in if you want to learn to integrate effective and ethical data governance in your company.Here are three reasons why you should listen to this episode:Find out how Adobe and Moody's Corporation integrate data governance.Learn how Adobe and Moody's Corporation utilize data governance to achieve their company goals.Discover how data governance can help companies succeed in today's market.Episode Highlights[03:09] Moody's Corporation and Data Governance Ryan: “I always say push versus pull. It's a journey. You have to start there.”Moody's Corporation welcomed data governance to their company because they believe it would be helpful for business. As a result, they found an advocate for data governance and thought of using it to solve business problems.Any company interested in integrating data governance should consider building the following: standards and policies, business partners, advocacy, and real governance.Once these are in place, form a data governance team to help solve real data-related business problems.Focus on the mantra, “success breeds success.”[04:13] Digital Asset Governance and Data GovernanceJoe: “Fish with a smaller fish to get a bigger fish.”Adobe started small and ended big by building data governance around the company's goals.It grew exponentially as more and more people heard and saw the data-related efforts the company was doing.The people could enrich the company because it dedicated its time to guiding them, providing them with playbooks, and facilitating their work.[07:16] Data, Water, and CakeJoe believes that data is like water. You trust the source that the water is clean.He adds that data is a component of a cake. The top layer where the frosting sits pertains to the business layer (e.g. process flows, business rules), the one people see.Below the frosting are the data products. The final layer is the data lineage.The three layers compose every company's data governance. They are assets that draw customers in and protect them.Data governance should always be customer-centric.[10:34] The Future Of Data GovernanceSociety has moved from wanting more data to trying to solve the problem of excess data. Hence, Joe believes that over the next ten years, people will start labeling and organizing data.Joe: “The groundwork is there. But I think there's just gonna be more and more and more and more data.”Ryan agrees that there is a ton of data in society today. So, the challenge for people now is defining meaningful and not meaningful is critical.He adds that automation will improve. Scanning databases and grading data lineage could become automated in the future.Ryan: "You're never done with data governance. We must realize this isn't going away. This is something we're going to have to continue doing."About Joe and RyanJoe Wallace is the senior manager...

Data can drive game-changing business decisions, but inconsistent data can do the opposite. The world of data has come a long way, but we still see businesses with problematic data reporting, which leads to their eventual downfall. The more we use data, the more we need to see it as both an asset and a responsibility. In this episode, our host, Jay Militscher, invites Stijn Christiaens, Collibra's very own Chief Data Citizen, to explore the topic of data citizenship and what it means for companies and data professionals. They will dive into what it means to be a data citizen and how to be intentional about data usage. Stijn also shares Collibra's growth over the years and showcases the importance of continuous improvement as data citizens. They also discuss the upcoming Data Citizen Conference and what it means to thrive with data. By listening to the episode, you will: Learn about why correct data handling is critical for businesses to thrive in today's world. Discover the meaning and context of data citizenship. Understand the value of different kinds of data literacy skills in an organization. Find out what questions to ask when using data to create and develop products. Pick up insights on how data drives continuous improvement. Want to know more about how to be a better data citizen? Tune in to discover the what, how, and why of being a data citizen.

AI is no longer for data scientists only. Most businesses have made AI tools part of their workflow. For example, we've seen chatbots, automated emails, and the like. As we embrace artificial intelligence, we have to discuss it. What is AI? What is it not? Should we use it for everything? In this episode, Sarah Hoffman, VP of AI and Machine Learning Research in Fidelity Investments, defines AI and its impact on our lives. She also describes the ethical challenges of data bias and what people are doing to overcome it. Finally, Sarah explains why diversity and prejudice are significant concerns in AI development. Tune in to this episode to learn how AI pushes for innovation.  Here are three reasons why you should listen to this episode:Discover artificial intelligence as a new approach to learning and training.  Learn how AI is a reflection of our own beliefs and understanding.  Understand the relevance of diversity in the field of artificial intelligence. ResourcesConnect with Sarah on http://linkedin.com/in/sarahfhoffman (LinkedIn) and http://twitter.com/sarahfhoffman (Twitter ) Know more about https://fcatalyst.com/observations/design (FCAT) Be part of https://rhok.ca/ (Random Hacks of Kindness) Episode Highlights[00:47] AI and ML Research at FCATThe Fidelity Center for Applied Technology (FCAT) has a long history of innovation and commitment to technology. Sarah: "We invest deeply in technology. But we've also always recognized that technology is just a tool. It's really how we apply it that matters."  FCAT develops platforms and products to empower the next generation. Sarah is a part of FCAT's research team. They explore the future of artificial intelligence (AI). [02:29] Defining AISarah uses AI and machine learning (ML) interchangeably. ML refers to code learning from data.  It produces answers based on stored information to make predictions. AI is math, not magic.  [03:43] AI in the Finance World FCAT provides services that harness AI's true potential. Financial services use AI tools often. Many people use chatbots, robo-advisers, and automated email responders. Several companies have adopted personalization and sentiment analysis. Models need to adjust when something changes in the world. [06:46] Data Ethics Concerns AI learns biases through data.  Ethics boards address ethical issues regarding AI projects and decide whether a problem needs AI. Fairness and explainability tools are available to protect against inadvertent biases.  Using AI can enhance how we train people and use fairness and explainability tools.  AI tools can help with issues regarding biases.  [10:25] Automatic Writing and Coding Multiple tools are now available to help you automatically write and code. Some tools can write code for you. The system is not perfect, but it's a good way for new developers to begin. Artificial intelligence can speed up coding for experienced programmers. AI tools are limited in terms of fact-checking. It can help with brainstorming, but it's essential to be critical regarding the data an AI provides. [16:04] Democratizing Innovation  The field of no-code/low-code has improved over the years.  We must democratize innovation to share ideas with everyone. [19:57] Education and Machine LearningEach individual has their preferred learning method. For instance, some people don't learn well in classroom settings.  Artificial intelligence offers another approach to learning.   AI can simplify jargon and make knowledge more accessible to a broader range of people. [22:20] Inclusivity in AI AI tools provide feedback on how to use inclusive terms when speaking or writing.  AI biases reflect our assumptions and prejudices.  Sarah: “AI tools are showing us the AI bias. Maybe we can start thinking about it for ourselves and think about 'Do we have this bias?'...

Data analysis, data science, and machine learning. The boundaries between these three may not be apparent, but these fields are related and interconnected. So it's possible to start a career in one and dabble with another. Data has made it easy to connect and acquire information. However, we must be vigilant in upholding privacy. In this episode, Gretel De Paepe, senior data scientist at Collibra, shares what she's learned in her data career. She tackles the importance of data in our lives and its incredible value — in the present and the future. Lastly, she tackles myths on artificial intelligence and machine learning. Tune in to the episode to learn how to handle data correctly. Here are three reasons why you should listen to this episode:Find out what inspired Gretel into pursuing data science. Learn how to appreciate data in making our lives better from both the average user's and company's perspective. Go beyond data bias and our misconceptions around artificial intelligence and machine learning. ResourcesConnect with Gretel on https://www.linkedin.com/in/greteldepaepe/ (LinkedIn). Episode Highlights[01:02] Machine Learning Projects at CollibraCollibra offers many services to their customers. Data classification helps companies classify fields that contain personally identifiable information (PII) data. Asset recommenders give a list of recommendations based on one's datasets. Similarity detection looks for similar assets to prevent potential duplication and keeps the database clean. [02:42] Defining Data Science, ML and AIData analysts looks at the data to provide a data-driven answer for a business question.  Data science deals with statistical modelling. The leap from data science to machine learning (ML) is small because machine learning is one way to model data. ML is simply a tool in the data science toolkit.  [04:51] Gretel's Data JourneyGretel's progression from data analysis to data science was a natural process. When solving different challenges, you must explore other techniques and build up your portfolio. She invested time and money into learning about machine learning. [10:19] Gretel's Natural Interest in Data ScienceGretel treats data analysis like a hobby. She easily loses herself in a project because she's interested in data science. Gretel: “Usually when I start with a project, there's not much information yet. It's sort of, “Oh, we may wanna do something in this area. But we don't really know yet what it is.” And so, the whole exploration phase of trying to identify what it is that we could do, what techniques we could use. And compare them, just try them out and compare them. It's a creative process.” [14:05] How Data Gives Value to ConsumersWe use data in statistics. Data is used often in our daily lives and provides many benefits. [19:24] The Myths and Unnecessary Hype around Data ScienceMarketing for artificial intelligence should focus on the fact that it's only artificial.  A machine's algorithm is limited by what it's trained to do. [23:26] Data BiasGretel: “If you have a bias in your data, you will have a bias in your model. So your model is indeed only as good as the data that you train it on.” Big tech companies open source their models, architectures, and patent packages. However, their data isn't. Obtaining data that's vast and also diverse is a challenge. Security has to be built-in from the start to ensure the obtained data isn't biased. [26:23] Auto-MLAuto-ML only works well when the hyper parameters are already known.  Computer vision enables the detection of objects in images equal to or sometimes better than human accuracy. Another breakthrough was also seen in NLP but language is more complicated than pictures since it's constantly evolving. [31:03] Data Science in the Next Five YearsPeople will see value in combining ML with privacy protection. Gretel: “Machine learning is a little greedy beast. It needs a...

The topic of sustainability has undoubtedly gained massive traction and momentum across industries over the past years. According to Martin Weirich, ESG is more than a buzzword and a PR trick — businesses have realized the beneficial impacts of sustainable models. From this, the term ESG or Environmental, Social, and Governance has emerged — and it's here to stay in the hopes of a better future for the world. In this episode, Martin Weirich, Partner Financial Services Management Consulting at PwC, discusses the basics of ESG. Martin delves into the regulatory aspect of ESG and how it can help make the world a better place. He talks about shifting the perspective and the future trajectory of ESG regulations. He also shares the most significant challenges companies face and how to navigate them. Tune in to the episode to understand how ESG is changing the ways of companies and the world's future. Here are three reasons why you should listen to this episode:Learn the three aspects of ESG. Discover the impact ESG makes on companies and the world at large. Find out Martin's prediction on what the ESG landscape would look like five years from now. Resourceshttps://www.pwc.com/ (PwC) Connect with Martin on https://www.linkedin.com/in/martin-weirich/ (LinkedIn) Connect with Jay on https://www.linkedin.com/in/jay-militscher/ (LinkedIn) Episode Highlights[01:19] What is ESG?ESG stands for Environmental, Social, and Governance. The environmental aspect includes concepts around climate, biodiversity, energy consumption. The social aspect concerns equal opportunities, human rights, health and safety, etc. Governance is about determining good governance and dealing with topics from an organizational standpoint. [02:18] The Regulatory AspectThe European side has already committed politically to specific ties they want to achieve as a region by 2030. There's a new required regulation influencing different sectors to support the political world to reduce greenhouse gas emissions and move toward renewable energy. The regulators began with the financial services sector because it deals with the orientation of capital flows.  Achieving the requirements also requires acquiring information (financial and environmental advocacy) from investee companies. These are not only regulations for bureaucracy's sake but to make the world a better place. Martin: "I think the dimension has a prompt. It's not only doing a tick box exercise from a regulatory perspective but also thinking out 'How can my products and my services help contribute to the overarching goals that we have all set?'" [06:26] More than Just a PR StatementA lot of companies used ESG as a marketing instrument in the beginning.  However, these companies soon realized that there's also public transparency enforced by regulators, clients, investors, and associations. Mislabeling, such as green-washing, is a significant risk from a reputational and management perspective. The regulations have defined standards and metrics to make ESG initiatives comparable across different industries. Many companies have shifted from being very marketing-driven to producing substance first and then being vocal. [10:10] Diversity in Companies' Board of DirectorsA diversified board is a great step towards achieving the governance aspect of ESG. Many corporations have intrinsic motivation to have diverse views on the boards. The US is leading on the topic of diversity. The European side doesn't have a detailed discussion of what a diversified board should look like. There's a push to have internal discussions and debates within firms about living up to this diversity standard. It's not realistic to change everything at once. It's more about defining a transition plan towards aligning on the targets and making it public. Martin: “The diversity element is just one element that's really helping to spark discussions and to get corporations and leaders thinking what...

The issues our society face today are increasingly complex and urgent. The rise of technology and the impact of the pandemic has put the spotlight on our growing social and environmental crises. But these crises are an opportunity for companies to rise up and show their worth. Now more than ever, companies are called to shift their solutions and initiatives in a way that will positively impact society at large by engaging in collaborative and holistic solutions. This way, they foster a more responsible corporate environment and create a sustainable future for all. In this episode, Melissa Mavlanova-August, the Global Head of Equity and Impact at Collibra, discusses the link between ESG and DEI. Melissa shares the initiatives and programs Collibra organizes to promote social and environmental awareness across the company. She also discusses the work involved in ESG and DEI career paths and the importance of storytelling in sustainable change management. Tune in to the episode to understand the impact incorporating ESG and DEI can have for creating sustainable and ethical companies. Here are three reasons why you should listen to this episode:Learn the meanings of ESG and DEI and the direct link between them. Discover how companies can shift to a sustainable social and environmental focus. Find out how to get into the ESG and DEI career paths. Resourceshttps://www.collibra.com/us/en (Collibra) https://bluedot.global/ (BlueDot) https://www.bluedotlaw.com/public-benefit/ (BlueDot Public Benefit Reports) https://www.teachfirst.org.uk/ (Teach First) https://www.accenture.com/ph-en (Accenture) https://www.amazon.com/Setting-Table-Transforming-Hospitality-Business/dp/0060742763 (Setting the Table) by Danny Meyer Connect with Melissa on https://www.linkedin.com/in/melissamavlanovaaugust/?trk=public_profile_browsemap&originalSubdomain=uk (LinkedIn) Connect with Jay on https://www.linkedin.com/in/jay-militscher/ (LinkedIn) Episode Highlights[01:56] Environmental Social Governance (ESG) and Diversity Equity Inclusion (DEI) at CollibraESG is about ensuring a sustainable business that's well-protected for the future in terms of its practices and human resources. Before formally starting their ESG efforts, Collibra's DEI-related work had shifted its focus on corporate social responsibility.  They realized that there is a direct link between ESG and DEI. Melissa's team looks after everything — the planet, people, and economy. [03:48] Employee Resource Group (ERG)Many of Colliibra's appetite for environmental, sustainability, and DEI work has come from their employees. Collibra had the environmental community, Planet Collibra Community, before formally establishing an ESG team. They rebranded ESG to "communities" to focus more on the human touch.  Collibra has nine DEI-related communities that foster a sense of inclusion and accountability. [05:08] Shifting to an Environmental FocusThe pandemic has brought the environmental crisis to the forefront of media and industries. There is a direct link between system inequality, systemic change, and environmental inequality. Environmental crises impact marginalized communities most. Collibra's growing sense of environmental responsibility led them to formally establish ESG and DEI into their framework. [06:41] Planet Collibra Community's Earth Month ProgramsFor Earth Month, Collibra organized an employee-led program aiming to promote environmental consciousness and awareness across the company. At the Reunited Company Employee Conference, employees built a water filtration system to be shipped to a country in need.  Planet Collibra focuses on practical, measurable value. [09:10] Collibra Swag StoreCollibra integrates ESG principles across the business into company plans and processes, such as the Swag Store The Swag Store is a product of Collibra's partnership with BlueDot. BlueDot only partners with providers who drive environmental...

Over the years, we've seen technology grow and how companies use the power of data to drive decision-making. However, we may be gathering more data than we can handle. Some companies may observe inconsistencies among data reports, leading to arguments and a lot of time wasted. This is where data governance comes in.   In this episode, Joseph Wallace, Senior Manager of Data Governance at Adobe, joins us to talk about the importance of data governance, like how it can deter arguments around inconsistent data and improves business processes. He shares how data governance works, and how Adobe has a vision to make trusted data discoverable. He also shares what he believes is the future of data governance and how we must look at data like how we consume water.  Tune in to the episode to dive deeper into data governance.  Here are three reasons why you should listen to this episode:Understand how data governance is defined, and how it can be used to improve business processes.  Learn why Adobe's data governance is rooted in making trusted data discoverable, and how the company defines trust, data, and discoverable.  Discover the water analogy of data governance and how data governance will continue to grow.  Episode Highlights[00:57] How Data Governance Started at AdobeAdobe implemented data governance around five years ago. This program started because the company started noticing inconsistencies among data reports.  The data governance program began by defining how metrics were created and calculated, and what they mean.  The initial point of their data governance program was to avoid arguments over conflicting data by creating an official source of truth. The more the program has grown, it has decreased storage costs and computing costs. It can also drive new insights and new revenue opportunities.   Joe began looking at how many people are looking for data and how long they are looking.   Joe: We've spent 20, 25 years saying ‘data, data, data, gimme the data. I want to analyze the data. We're gonna drive with data. We're gonna do things with data.' And now we're here with mountains of data and we have no clue what to do with it. We have no real knowledge of where it is and how to use it. What's the most efficient and effective way of using it? That's the real value proposition of data governance. It's protecting it. It's making it searchable. It's helping people use it in the right ways at the right times for the right purpose.  [07:06] How To Define Data Governance For Joe, data governance is about making trusted data discoverable.  For Adobe, trust means customers are using their products securely and know that if there's an issue, it could be recovered.  Trust also involves operational data used for operational decisions that drive the company.  Joe explains that their data governance program is the hub of the wheel. Its spokes include privacy, corporate governance, and legal components. [10:35] How Adobe Defines Discoverable Data Data covers actual tables and columns, assets like IP, and both customer and Adobe content.   Joe prefers the term “digital asset governance,” since data can mean different things to different people.  In order to make data discoverable, Adobe uses a trust score and a prioritization model. The trust score looks at how people are using products, and how often.  Right now, the prioritization model is undergoing changes to prioritize customer data.  [14:30] How Adobe's Data Governance Team FunctionsInitially, Joe needed to convince people why data governance is important. Now, people are coming into the team on their own.  Over time, Joe has created different templates and playbooks built from previous cases.  He helps empower teams and people throughout the business to do their own data governance.  Joe: “You can't govern it if you...

As companies grow and their market expands, their systems and processes become more complex. Managing data assets can be overwhelming without proper knowledge, organization, and mastery. This is where the concept of a data office comes in handy. In a time when data is more valuable than ever, it is imperative that a company understands how to make it work for them. It might be time for you to consider forming a data office within your company, particularly if your company: is in a position of rapid growth, onboards employees daily, is expanding their market, and/or deals with systems and processes that may be out of date. In this episode, Stijn Christiaens, Founder and Chief Data Citizen at Collibra, joins us to discuss the importance of handling data and starting a data office. He explains what inspired him to begin creating the data office within Collibra, and how this concept may pave the way for future companies.  Tune in to the episode to further understand how to build a data office for your business.  Here are three reasons why you should listen to this episode: Understand the importance of data in a growing company.  Identify if your company needs to build its own data office. Learn from Collibra's journey of building a data office. Jay Militscher: “It meant to me that data and facts inform whatever point you're making at the moment. Are you making a recommendation to buy something? Where's the chart? Meaning data, to back up that decision. Are you delivering a critique on something? Again, where's the data to back up an otherwise subjective opinion.” Episode Highlights[07:47] More People Means More DataCollibra experienced rapid growth in its company, onboarding more people than the system could handle. As more people filter into the company, more data is added to the system. This increase in staff also implies an increase in customer interactions.  [08:19] An Expanding MarketFor Collibra, rapid internal growth meant growth in the market.  They needed to streamline their transition from data governance to data intelligence. Stijn believes that the growth in people and in the market means growth in data, which needs to be mastered. Stijn Christiaens: “And, in that sense, we also said, okay, if we set up a data office now because we need it, right? Because systems and processes will also have the added benefits if we do this right to continue to lead our customers. And then you start to experience, really, also what some of your customers experience, right?”  [09:58] Leading the WayStijn took on the challenge of accepting the new role of becoming the “data boss” to lead the way not only for Collibra but for future organizations.  “Data Office 2025” is realized by Stijn and his team for future organizations that will face similar challenges as Collibra is experiencing.  This includes dealing with new data technology and new tools for data stakeholders across the business. Stijn Christiaens: “All organizations, over time, we need to get better at mastering data assets. So all organizations, just like they have a chief financial officer. They will have a data boss or somebody responsible for data and maybe a data office just like their finance and HR, let's say. So, we saw a trend, and then we said, okay, we can actually do this.” About StijnStijn Christiaens is the co-founder and current chief data officer at Collibra. He's been involved with the company for 15 years and spearheaded the creation of the data office for Collibra. Enjoyed this Episode?If you did, be sure to subscribe and share it with your friends!  Post a review and share it! If you enjoyed tuning in, then leave us a review. You can also share this with your friends and family. This episode will inform them of the importance of data and building a data office for your company's future. Have any questions? You can connect with us on https://www.linkedin.com/in/jay-militscher/...

Data is a land mine for growth, and more businesses are realizing the great potential it holds. The value and insights from data have seen a rise in demand within organizations, and with this rise comes the expectation of a rapid turnaround time. However, this poses a significant challenge to central data teams, who handle data management and analytics. This led to the concept of data mesh, a decentralized approach that reduces friction and gives business domains the ability to quickly access and query the data they need. In this episode, Sonali Bhavsar, Managing Director for Global Data Governance at Accenture, joins us to talk about the four pillars of data mesh. She discusses how companies can start applying data mesh to their workflows. Sonali also shares how Accenture helps its clients achieve data-led transformations. Tune in to the episode to know more about data mesh, its significance and some tips to apply it to any business. Here are three reasons why you should listen to this episode:Learn about the four pillars of data mesh. Understand why a federated approach is favored over a centralized system. Discover how Accenture walks the talk in data mesh and data-led transformation. Resourceshttps://player.captivate.fm/episode/cf62005f-26cf-4c50-b601-627d22bee79f (Bonus track episode on data mesh) Connect with Sonali on https://www.linkedin.com/in/sonalibhavsar/ (LinkedIn) Episode Highlights[00:33] The Four Pillars of Data MeshData mesh is an approach to reduce friction in data workflows in order to maximize the value of data. Its four pillars are data as a product, domain ownership, self-service data infrastructure, and federated computational governance. [03:47] Federated vs. Centralized ApproachA federated approach allows your line of business to make decisions on their operation and what they value to meet regulatory obligations within their jurisdictions. A centralized approach has not been a sustainable model for the longest time. However, it's most likely to work for an isolated, less hierarchy-driven organization. Traditionally, data governance decisions made outside of the business lineup and restructuring can lead to delays or unwanted results. For more complex organizations, each line of business might need to implement data governance in a certain way that may change or evolve within those lines. [07:14] Self-service Data Infrastructure A big wave of data literacy is happening and the end goal is self-service. Self-service means that the consumption of citizens' data, whether internally or externally, is built on trust. [08:13] Data Mesh TrendsData mesh is not a new concept, but it's becoming a hot topic. There is now a stronger awareness of data as a product, which was more theoretical before. The decentralized form of data ownership came about because businesses now see more value in data and want to maximize it. Sonali: “You really want to support that end data citizen to be flexible to use the data that they want to use it as, versus going through permissioning and asking for that data.” Some components will remain centralized. Federated simply means the catalog of data products leans toward business ownership rather than a centralized data ownership.  There is a big pivot on determining data quality and its lineage, which affects whether different industries can use data and what data product can or cannot be made from it. [11:59] Businesses' Data Mesh Readiness Industries such as financial services, insurance, and pharmacy already apply data mesh. High-tech companies are following suit. The line of businesses and the industries they're in are altogether getting disrupted. [14:34] Readiness to Adopting a Self-service InfrastructureSelf-service is about firms investing in data catalog and data quality tools. Formerly, this was only done to observe regulatory protocols. Financial services have been always ahead of that curve because of regulations....

Data mesh is a relatively new concept that aims to reduce friction in maximizing the value of data. It distributes data control to different business domains that have experts in the data relevant to them. A catalog of data products contributes to the data owners' efficiency in curating and analyzing their data for business insights. In this episode, Luis Romero, the Product Marketing Director at Collibra, talks in-depth about the four pillars of data mesh and how it can empower businesses. Jay Militscher, the Head of Data & Analytics at Collibra, also shares Collibra's humble beginnings in executing data mesh and how they hope to improve their already robust system. Tune in to the episode to know about data mesh, its significance, and how to utilize it within your organization. Here are three reasons why you should listen to this episode:Understand the significance and the four pillars of data mesh. Learn how Collibra effectively implements data mesh. Discover how to get started in bringing in data mesh within organizations. Resourceshttps://www.collibra.com/us/en/blog/data-mesh-101-a-straightforward-overview-of-the-hottest-topic-in-enterprise-data (Data Mesh Blog Series) Connect with Luis on https://www.linkedin.com/in/luis-romero-5a771520/ (LinkedIn) Connect with Jay on https://www.linkedin.com/in/jay-militscher/ (LinkedIn)  Episode Highlights[01:50] How Data Mesh Can Help Business DomainsIT and data teams are not the experts on the data coming from the other departments. It's best to have data in the hands of experts who will manage, curate, and cleanse data. Eventually, they turn the data into a product for its consumers. Analysts and business users waste a lot of time finding the data they need, and sometimes they even find difficulty in trusting the data. Data should be pre-packaged and available in a catalog for anyone who needs it, making it easier to verify and extract the right insights from it. The four pillars of data mesh are data ownership, data as a product, self-service data infrastructure, and federated governance. [05:50] Domain OwnershipMost organizations have multiple business domains such as finance, engineering, marketing, etc. Luis: “We should instead put that data into the hands of the true data stewards right within these domains.” The different business domains are best positioned to manage, curate, and make the data fully and readily available to be consumed by the business. [06:48] Data as a ProductData owners with full knowledge and expertise about the data should treat data like a software product. A software product has a vision, strategy, and life cycle. We should treat data in the exact same way.  Treating data as a product means providing all the necessary facts and documentation. So that when it's in a catalog, it's ready to go. [08:25] Self-service Data InfrastructureLuis observed that 99% of their customers complained about their complex data landscape because they have their data across different sources. Having various data sources can overwhelm companies when they retrieve and process data — more so when turning it into a usable product. Luis: “We got to figure out a way to remove the friction from both the data producers and the consumers, and make it easy for them to go and find that data, bring that data together, understand the quality of the data, and again put it out there in a data marketplace, a data catalog, but again, make it very, very self-service.” Make data as self-service as possible by leveraging all kinds of cloud technology. Enterprise data catalogs can enable a one-stop shop for retrieving your data across all data sources. Set up a  data marketplace where all the users can go to find certified data sets. [11:07] Federated GovernanceLarge enterprises have acquired many independent business entities across multiple acquisitions over several years.  A healthy balance between reducing risk and...

Data ethics may be a relatively new field, but its underlying principles are nothing new. Currently, regulations on data ethics are lacking, but organizations are still making data ethics a priority. Ethical data management is a must in today's data-driven world.  In this episode, Anna Hannem, the director of Data Ethics & Use at Scotiabank, joins us to discuss the importance of data ethics, the best practices to ensure the ethical use of data across your organization, and her insights on the growing field of data ethics. Tune in to the episode if you want to know how you could integrate data ethics as part of your company's culture. Here are three reasons why you should listen to this episode:Find out why Scotiabank puts a premium on data ethics. Learn how Scotiabank effectively implements data ethics within its organization. Discover how the field of ethical data management is growing and where it will be in a few years. ResourcesConnect with Anna over at https://www.linkedin.com/in/anna-hannem-mba-pmp-a73aba17/?originalSubdomain=ca (LinkedIn) Episode Highlights[02:14] The Significance of Data EthicsScotiabank's focus on data ethics started only a couple of years ago. The concept of ethical data management isn't new, but the field or profession is. Our world has become virtual and digital, making it data-driven. We can now feel the vast implications and impact when organizations use our data. Many big companies made mistakes that weren't necessarily illegal or had malicious intent but still led to breaching customer trust. Scotiabank is committed to upholding customer and public trust through data ethics. [04:48] How Scotiabank Practices Data Ethics Scotiabank instills data ethics principles into its culture, processes, and procedures to educate within the organization and the industry as a whole. Anna: “But in fact, data isn't black and white, right? It's how we collect it, where we collect it from, and how we're intending to use it.” Scotiabank implements an ethics assistant, an AI-powered tool that guides its model developers by giving insights on the proper use of data. In the US, some financial organizations negatively impact minority populations. The algorithm may be the problem despite bias, diversity, and discrimination training. The analytics team should be able to work with the business team, who then makes sure the customers are on the same page on what went into the algorithm for the unwanted outcome to happen. Scotiabank is guided by its main ethical principles of being fair, transparent, and striving to safeguard customer data. They treat accountability seriously. [16:56] Developments in Scotiabank's Data Management and Ethics Even without regulations on data ethics in North America, people are receptive to the processes and tools to instill data ethics. Anna observes that people are open to doing extra work to do what's ethical when it comes to customer data.  Make processes for data ethics easier so that people are inclined to do it repeatedly.  Data ethics started in Scotiabank's Chief Data and Analytics Office before being implemented in other parts of the organization. Anna wished they already knew other areas that could have benefitted from their processes and implemented them there sooner for faster scalability. [22:06] The New But Growing Space of Data EthicsThere's no degree yet for purely data ethics, but some universities offer it as part of their data analytics course. Scotiabank is partnering with universities to help them build programs on data ethics. Anna: “There are not that many thought leaders yet in this space, and so as regulations are coming, we want to be influencing that, and we want to already be ahead of some of these curves and instilling best practices and learning from them ahead of time so [we know what worked well and what didn't].” Jay: “What's the safest way, the best way, the most appropriate way to drive value? And

As technology grows, we've come to recognize the power of big data: how it influences company policies, consumer choices, and even government decisions. Data should not be just for profit — it should have an ethical and moral basis, which is where the importance of data ethics comes in. If you'd like to know more about data security and its ethical considerations, you're in for a treat this week.  In this episode, Simla Sivanandan, Senior Manager of Data Intelligence at Collibra, joins us to talk about the importance of data ethics and how Collibra upholds data ethics within their organization. She also shares how the real problem is unconscious bias when dealing with machine learning (ML) and artificial intelligence (AI).  Tune in to the episode to dive deeper into data ethics and unconscious bias. Here are three reasons why you should listen to this episode:Gain an understanding of what data ethics is all about. Discover the significance of unconscious bias in handling data. Find out how Collibra strategically instills data ethics within the company. ResourcesAn https://physicsworld.com/a/covid-19-pandemic-has-made-weather-forecasts-less-reliable/ (article) on Lancaster University's study on why weather forecasts were less reliable after the COVID-19 pandemic Connect with Simla over at https://www.linkedin.com/in/simla-sivanandan/ (LinkedIn) Episode Highlights[01:20] Connecting Data and EthicsSimla initially found the concept of data ethics unnatural. Data is precise, while ethics are very subjective.  Ethics may seem simple, like doing the right thing, but what's right can differ for different people. Simla: “You see the power of data, where people are using that to make decisions that affect your life, your life quality, and all of that. So, we, as data professionals, always see the power of data. I think, as data citizens, it's our responsibility to use it ethically [and] wisely.” During the vaccine shortage at the start of the pandemic, the government used data to determine who was the priority, which has ethical implications. [04:45] Unconscious BiasData ethics is much bigger than machine learning (ML) and artificial intelligence (AI), which businesses use to personalize the customer's online experience. Companies must be aware of the purposes and risks involved in asking customers for their personal data. Simla: “To me, really, the gold standard is: If I'm working in a bank, am I comfortable banking with them? If I'm working in an insurance company, am I okay to purchase that? That kind of tells me: Am I okay with the way they are treating my data, right? That's where I am that it's not just ML or AI.” Simla believes that the conversation around ML and AI involves unconscious bias. There are cases wherein we have no control over the data, even if we understand why it's happening. Unconscious bias is a vital conversation to have in data ethics. Simla: “Exclusion creates bias, and that might be unconsciously happening because we are not thinking through or we're not picking a big enough sample set. That's where I'm coming from. So, it's always important as a data professional to be aware of this, right? As I limit my sample set, it can have unintended consequences, and we should address that.” [10:18] How Collibra Strategically Instills Data Ethics Collibra is guided by its core values: being open, direct, and kind. The company strives to communicate directly, thoughtfully, and kindly. Collibra always thinks about how their work matters and its impact on many people and industries, which guides their ethical value system. Data ethics is everyone's responsibility, not just companies and governments. Social media should recognize its power and strengthen the moral framework within its algorithm to protect consumers instead of prioritizing more clicks and users. About SimlaSimla Sivanandan is the Senior Data Intelligence Manager at Collibra. She's a data...

Join Jay Militscher, Head of Data & Analytics at Collibra, as he explores some of the hottest topics in the industry from building a data office, to ESG, to the ethical use of data, and beyond. In this five-part series, industry leaders from around the globe share their best practices, learnings, and predictions for the future.  But it doesn't stop there…we also have five bonus episodes in this series that feature our very own Collibrians. These “Inside Collibra” episodes show how Collibra's very own Data Office is tackling these complex issues.  Welcome to The Data Download!