Data Radicals

Saul Alinsky's book Rules for Radicals held significant lessons for grassroots movements and political activism when it was published in 1971. It also inspired the title and theme of this podcast. In his book, Saul outlines approaches for unifying people and motivating them to work toward a common goal. Today, these same strategies can be used for data culture change management, triggering transformative action within organizations. Saul was an American activist and political theorist who lived from 1909 to 1972. His work organized impoverished communities and gave them tools to drive social change, and won him national attention and notability. In the final episode of the season, Satyen sits down with a ChatGPT-infused version of Saul to discuss the role of data in driving social change, the application of community organization tactics in corporate settings, and the key principles from Rules for Radicals.--------“On the global stage, data analytics and humanitarian efforts is akin to having a crystal ball. It's not about predicting the future, but about making informed, timely decisions that can save lives. The possibilities are indeed limitless. With data and analytics, we're not just changing the game. We're rewriting the rules and designing a better playbook for humanity.” – Saul GP Talinsky--------Episode Timestamps:*(03:57): Bridging community organizing with data science*(12:46): Empowering teams: Upskilling organizational agility*(14:35): Democratizing data and crafting a culture of insight and empowerment*(17:17): The timeless role of data in driving social change*(20:54): How to unlock societal transformation with data and analytics*(26:26): The evolution of radical change--------SponsorThis podcast is presented by Alation.Learn more:* Subscribe to the newsletter: https://www.alation.com/podcast/* Alation's LinkedIn Profile: https://www.linkedin.com/company/alation/* Satyen's LinkedIn Profile: https://www.linkedin.com/in/ssangani/--------LinksRead Rules for Radicals

The rapid progress in AI technology has fueled the evolution of new tools and platforms. One such tool is a vector search. If the function of AI is to reason and think, the key to achieving this is not just in processing data, but also in understanding the relationships among data. Vector databases provide AI systems with the ability to explore these relationships, draw similarities, and make logical conclusions. Understanding and harnessing the power of vector databases will have a transformative impact on the future of AI.Edo Liberty is optimistic about the future where knowledge can be accessed at any time. Edo is the CEO and Founder of Pinecone, the managed database for large-scale vector search. Previously, he was a Director of Research at AWS and Head of Amazon AI Labs, where he built groundbreaking machine learning algorithms, systems, and services. He also served as Yahoo's Senior Research Director and led the research lab building horizontal ML platforms and improving applications. Satyen and Edo give a crash course on vector databases: what they are, who needs them, how they will evolve, and what role AI plays.--------“We as a community need to learn how to reason and think. We need to teach our machines how to reason and think and talk and read. This is the intelligence and we need to teach them how to know and remember and recall relevant stuff. Which is the capacity of knowing and remembering. The question is, what does it mean to know something? To know something is to be able to digest it, somehow to make the connections. When I ask you something about it, to figure out, ‘Oh, what's relevant? And I know how to bring the right information to bear so that I can reason about it.' This ping pong between reasoning and retrieving the right knowledge is what we need to get good at.” – Edo Liberty--------Time Stamps*(03:13): How vector databases revolutionize AI*(14:13): Transforming the digital landscape with semantic search and LLM integration*(28:10): Exploring AI's black box: The challenge of understanding complex systems *(37:02): Striking a balance between AI innovation and thoughtful regulation*(40:01): Satyen's Takeaways--------SponsorThis podcast is presented by Alation.Learn more:* Subscribe to the newsletter: https://www.alation.com/podcast/* Alation's LinkedIn Profile: https://www.linkedin.com/company/alation/* Satyen's LinkedIn Profile: https://www.linkedin.com/in/ssangani/--------LinksConnect with Edo on LinkedInWatch Edo's TED Talk

Folks in the data space are familiar with the concept of data literacy. However, a new idea is on the rise: business literacy. Whether folks sit in product, marketing, or commercial, there needs to be a productive balance between understanding business context and technical expertise of each department. This shared comprehension means ideas are more likely to be deployed and productionalized because everyone has deeper domain knowledge and business understanding.Sanjeevan Bala is making business literacy a top priority at his organization. He is the Group Chief Data and AI Officer at ITV, an Alation customer. There, he is responsible for driving the digital data and AI transformation and leading an offensive growth strategy that enhances how they produce, promote, distribute, and monetize content. Sanjeevan is an international thought leader, has won numerous awards for his work, and was named the most influential person in data by DataIQ. Satyen and Sanjeevan discuss the idea of a Data Product Manager, the importance of business literacy, and the power of experimentation.--------“I think because we went down the data as a product notion, that leadership role was a Data Product Manager. Incorporate product thinking in the way in which data is developed, designed, and used. I think what's beautiful about product thinking is it's very well adapted and equipped for understanding competing objectives and competing needs. Creating methods by which you're trying to either align or prioritize those needs. But, critically allows you to prioritize around the right things because you're constantly looking at how do you make sure you can productionize and scale and realize the full value? What does it take to do that? That goes way beyond what you're doing in data. That gets into organizational change, that gets into last mile technologies that you may not have thought about.” – Sanjeevan Bala--------Time Stamps*(05:16): How to define your organizational identity*(07:26): The art of storytelling and data-driven leadership*(18:20): Harnessing experimentation to drive organizational change*(25:10): Data literacy versus business literacy*(42:17): Balancing innovation and regulation in AI*(44:41): Satyen's Takeaways--------SponsorThis podcast is presented by Alation.Learn more:* Subscribe to the newsletter: https://www.alation.com/podcast/* Alation's LinkedIn Profile: https://www.linkedin.com/company/alation/* Satyen's LinkedIn Profile: https://www.linkedin.com/in/ssangani/--------LinksConnect with Sanjeevan on LinkedIn

Whether you work in retail, healthcare, or CPG, data analytics is key to making your business stand out. You're able to find new sources of data, synthesize them, and then work with business folks to get better and better insights. Even with all of the advantages analytics offers us, sometimes there's hesitancy to invest in data. In sports, it's the exact opposite. The use of data is felt immediately in game wins, player selection, and gate revenue.Known as “The Real Moneyball guy,” Ari Kaplan has revolutionized sports through analytics and is a leading influencer in the area, as well as in AI and data. He helped create analytics departments for the Chicago Cubs, Los Angeles Dodgers, and Baltimore Orioles. Ari is now Head of Evangelism at Databricks where his team helped the Texas Rangers clinch their first World Series title. Satyen and Ari discuss data analytics in sports, how data intelligence platforms are shifting the landscape, and the concept of generation AI.--------“Even if we change nothing else, to be able to make better predictions of player development, finding what skills are better in the draft, predicting injuries and so on, that's part of the competitive advantages. How can we ingest this data? It's a ton of data. Terabytes of data every game, multiply that by dozens and dozens of teams at all levels around the world. Right now, teams are struggling to store it, process it on a daily basis. Teams that could do that faster will be an advantage. For listeners, if you're not in the baseball world, same idea. If you're in retail, CPG, healthcare, it's finding new sources of data, proprietary, nonproprietary. How could you synthesize it? Then, how can you start working with the business people to get better and better and better insights?” – Ari Kaplan--------Time Stamps:*(03:00): The birth of Moneyball*(10:11): How the Texas Rangers hit a data home run*(15:49): The next evolution: data intelligence*(27:17): Partnering for success in the ecosystem*(38:54): The role of AI in building the future*(41:29): Satyen's Takeaways--------SponsorThis podcast is presented by Alation.Learn more:* Subscribe to the newsletter: https://www.alation.com/podcast/* Alation's LinkedIn Profile: https://www.linkedin.com/company/alation/* Satyen's LinkedIn Profile: https://www.linkedin.com/in/ssangani/--------LinksLearn more about Raoul Wallenberg's fateConnect with Ari on LinkedInFollow Ari on X

When it comes to our relationship with technology, be like philosopher Friedrich Nietzsche and practice mindfulness. We usually think mindfulness means setting boundaries like screen time limits. However, we should think about the goals and values we want from technology, like greater human connection, improving efficiency, or driving knowledge. This introspective thinking enables us to be intentional about how and why we're using technology. Without mindfulness, instead of you driving the tech, the tech may be driving you. Nate Anderson lives by and continues to share Nietzsche's philosophies today. Nate is the Deputy Editor at Ars Technica, where he covers technology law, politics, and culture. He combined his high-tech background with a love of writing to freelance at publications like The Economist and Foreign Policy. Nate is also the author of In Emergency, Break Glass: What Nietzsche Can Teach Us About Joyful Living in a Tech-Saturated World. Satyen and Nate discuss forming positive connections with technology, saying “yes” to life, and what Nietzsche would have to say about tech.--------“Connection to other people is important. We use technology to create that connection. That might mean a Friday night game group over Zoom or Twitch or multiplayer with your friends. As long as you have the goal in mind, that's where it requires your creativity. That's where you're using the tools creatively to produce outcomes that you want in life. The problem with not thinking in a goal-directed way is that technology itself is not completely neutral. Technology has no goals of its own. It was created by people and companies who have plenty of goals and some of those don't necessarily take you to places where you would choose to go. That's why if you don't have a goal-driven approach to technology, you may find technology is actually driving you.” – Nate Anderson--------Time Stamps:*(04:25): Why Nietzsche? Why now?*(15:07): Offer agency, not just prescriptive rules*(24:17): The loneliness of technology*(27:51): Seeking that goal-driven place*(35:44): Producing actual value*(38:35): Satyen's Takeaways--------SponsorThis podcast is presented by Alation.Learn more:* Subscribe to the newsletter: https://www.alation.com/podcast/* Alation's LinkedIn Profile: https://www.linkedin.com/company/alation/* Satyen's LinkedIn Profile: https://www.linkedin.com/in/ssangani/--------LinksRead In Emergency, Break GlassConnect with Nate on LinkedIn

Thanks to GenAI, we have an overabundance of tools, models, and capabilities. However, the use and impact of these advancements is yet to be known. That's why in the age of technological innovation, traditional skills like fact-checking are more important than ever to ensure that the technology and predictions are correct. Guy Scriven, U.S. Technology Editor at The Economist, is on the frontlines of the AI explosion. In his tenure at the publication, he has served as a researcher and climate risk correspondent, and has grown his affinity for telling data-driven stories. Satyen and Guy discuss the role of data in journalism, instilling a culture of debate, and the unsexy – but critical – side of AI.--------“We've had this long period of experimentation and excitement. That's been basically marked by the supply side of AI just really ramping up. You've had loads of model makers releasing new models. You've had the cloud players buying enormous amounts of specialized AI chips. You've had thousands of AI application startups who are going to build on top of the model makers, who then use the AI chips from the cloud providers. You've had this boom in the supply side of AI. Now, the big question is whether the enterprise demand meets that and what shape it takes. I think we don't really have a good sense of that until at least the first couple of quarters of next year.” – Guy Scriven--------Time Stamps:*(02:22): Less reporting, more commentary *(13:32): Dataset discovery *(22:34): ChatGPT's hallucination problem *(34:38): AI headlines on the rise *(41:48): What's the next big AI story? *(46:10): Satyen's Takeaways--------SponsorThis podcast is presented by Alation.Learn more:* Subscribe to the newsletter: https://www.alation.com/podcast/* Alation's LinkedIn Profile: https://www.linkedin.com/company/alation/* Satyen's LinkedIn Profile: https://www.linkedin.com/in/ssangani/--------LinksConnect with Guy on LinkedIn

The best kind of data radical is one who knows how to balance their technical expertise with their fuzzy side. Skills like storytelling, empathy, and ethics are becoming invaluable in the tech space. The ability to balance both enables data folks to recognize patterns where others might miss them. This type of integrative thinking can guide people on their next investment, whether they're investing time, money, or resources. Scott Hartley is a global early-stage investor and author of The Fuzzy and the Techie: Why the Liberal Arts Will Rule the Digital World. His passion lies in emerging markets and big ideas that improve lives, particularly in financial services, health, supply chain, and logistics. Scott has served as a Presidential Innovation Fellow at the White House and has co-founded two venture capital firms: Everywhere Ventures and Two Culture Capital. Satyen and Scott discuss the techie and fuzzy sides of Silicon Valley, the advancement of tech, and how Scott chooses his next investment.--------“I love this thought around data collection and big data is one thing, it's collecting information. But, then turning that information into knowledge and into wisdom. In one part, can be done through unstructured to structured data, through things like LLMs that are enabling us to move out of the information noise into a bit more knowledge noise, and then maybe into wisdom specificity. I still think that there's a leap there that's going to be human-driven. Whether it's a person sitting there interpreting or it's a team of engineers thinking about the sensitivities, the data tagging. There are human decisions in the mix somewhere along that chain, as we're taking on structured data and turning it into structured knowledge and wisdom. All these things to say, that even these deeply technical infrastructure-level technologies, have elements of humanity in them.” – Scott Hartley--------Time Stamps:*(10:55): The genesis behind The Fuzzy and the Techie*(18:11): Subjectivity, structure, and bias*(20:17): Scott's investment focus*(30:09): The “tables-stakes economy” *(38:11): AI and public policy *(47:43): Satyen's Takeaways--------SponsorThis podcast is presented by Alation.Learn more:* Subscribe to the newsletter: https://www.alation.com/podcast/* Alation's LinkedIn Profile: https://www.linkedin.com/company/alation/* Satyen's LinkedIn Profile: https://www.linkedin.com/in/ssangani/--------LinksRead The Fuzzy and the TechieVisit Scott's websiteConnect with Scott on LinkedIn

Precision in technology is powerful. When it comes to services like Uber, people know the exact location of the driver and how much the trip will cost. Precision helps banks lend money to folks with bad credit, but who took the initiative of telling a bank when they would miss a payment. Precision can even help deliver urgent medical supplies via drones in countries that need it most. Precision in technology means users have total visibility on location, price, and competitors, and they're able to achieve better outcomes.Maddy Want is the VP of Data for Betting and Gaming at Fanatics. Maddy has over a decade of data product experience spanning diverse web and app services, and has served companies like Audible, upday, and Index Exchange. When Maddy joined Fanatics, she was responsible for creating the data strategy, hiring the data team, and partnering with tech. Satyen and Maddy discuss her new book, Precisely, data governance, and why precision matters.--------“We've gone to total visibility on location, total visibility on price, and ability to shop across competitors. To me, the big theme out of all of those things is it's not about the technology itself, it's not about drones, or it's not about auction mechanics like that power Uber. Those things are cool, but it's about the capability that it's given to the customers, or the patients, or whoever. The theme there is that they have more precision. They can be more precise about what kind of change they're requesting or they're affecting, and they can have an outcome that's much more tailored to them.” – Maddy Want--------Time Stamps:*(05:45): The disconnect between public policy and tech*(13:09): The focus on precision *(20:18): Writing Precisely*(29:50): Maddy's role at Fanatics*(39:27): Structuring the team *(47:19): Satyen's Takeaways--------SponsorThis podcast is presented by Alation.Learn more:* Subscribe to the newsletter: https://www.alation.com/podcast/* Alation's LinkedIn Profile: https://www.linkedin.com/company/alation/* Satyen's LinkedIn Profile: https://www.linkedin.com/in/ssangani/--------LinksRead Precisely: Working with Precision Systems in a World of DataConnect with Maddy on LinkedIn

With the rise of GenAI, LLMs are now accessible to everyone. They start with a very easy learning curve that grows more complicated the deeper you go. But, not all models are created equal. It's critical to design effective prompts so users stay focused and have context that will drive how productive the model is.In this episode, Matthew Lynley, Founding Writer of Supervised, delivers a crash course on LLMs. From the basics of what they are, to vector databases, to trends in the market, you'll learn everything about LLMs that you've always wanted to know. Matthew has spent the last decade reporting on the tech industry at publications like Business Insider, The Wall Street Journal, BuzzFeed News, and TechCrunch. He founded the AI newsletter, Supervised, with the goal of helping readers understand the implications of new technologies and the team building it. Satyen and Matt discuss the inspiration behind Supervised, LLMs, and the rivalry between Databricks and Snowflake.--------“This idea of, ‘How does an LLM work?' I think, the second you touch one for the first time, you get it right away. Now, there's an enormous level of intricacy and complication once you go a single step deeper, which is the differences between the LLMs. How do you think about crafting the right prompt? Knowing that they can go off the rails really fast if you're not careful, and the whole network of tools that are associated on top of it. But, when you think from an education perspective, the education really only starts when you are talking to people that are like, ‘This is really cool. I've tried it, it's awesome. It's cool as hell. But how can I use it to improve my business?' Then it starts to get complicated. Then you have to start understanding how expensive is OpenAI? How do you integrate it? Do I go closed source or open source? The learning curve starts off very, very, very easy because you can get it right away. Then, it quickly becomes one of the hardest possible products to understand once you start trying to dig into it.” – Matthew Lynley--------Time Stamps:*(04:21): The genesis of Supervised*(11:34): The LLM learning curve*(21:35): Time to build a vector database?*(31:55): Open source vs. proprietary LLMs *(41:35): Snowflake/Databricks overlap*(47:47): Satyen's Takeaways--------SponsorThis podcast is presented by Alation.Learn more:* Subscribe to the newsletter: https://www.alation.com/podcast/* Alation's LinkedIn Profile: https://www.linkedin.com/company/alation/* Satyen's LinkedIn Profile: https://www.linkedin.com/in/ssangani/--------LinksRead SupervisedConnect with Matthew on LinkedIn

The art of medicine happens when physicians combine data and knowledge to deliver better patient outcomes. A physician that relies both on guidelines and their learned experience is creating a culture of data and insights and improving the lives of patients. Whether you're a doctor or a data leader, knowing how to balance data and intuition will always drive better results.Dr. Bapu Jena is an economist, physician, and Joseph P. Newhouse Professor of Health Care Policy at Harvard Medical School. He bridges his professions to explore the economics of healthcare productivity and medical innovation. Satyen and Bapu discuss leveraging data in healthcare, applying AI in medicine, and measuring the innovation of doctors.--------“We have put a premium on the innovativeness of the technology. There could be a new molecule that attacks a pathway that has never been attacked before. If that molecule doesn't improve life expectancy or improve quality of life, then there's not a lot of value to me in that innovation, even though it's certainly innovative. I care more about whether or not it impacts patients' lives. The correlator to that is that you could have a medication which does not appear to be that quote, unquote, ‘innovative,' at all because it's just a reboot, in some respect, of other medications. But, it's taken in a way that people are more likely to be adherent to. Those types of technologies are sometimes pooh-poohed on, but they could be very valuable because what ultimately matters is the outcome of whether or not a person gets better when they're on that medication, not how innovative it is. This is also a problem when it comes to data-driven interventions, as well. Because, there's a lot of interest in AI and non-medical technologies, or non-life science technologies. The key there is you've got to demonstrate that there's some outcome benefit.” – Bapu Jena--------Time Stamps:*(03:23): Predictable randomness *(12:13): Data points tracking intensity of care *(25:48): AI in medicine *(31:29): The politics of standards of care *(38:41): The challenges of influencing change *(51:18): Satyen's Takeaways--------SponsorThis podcast is presented by Alation.Learn more:* Subscribe to the newsletter: https://www.alation.com/podcast/* Alation's LinkedIn Profile: https://www.linkedin.com/company/alation/* Satyen's LinkedIn Profile: https://www.linkedin.com/in/ssangani/--------LinksRead Bapu's book Random Acts of MedicineRandom Acts of Medicine SubstackListen to Freakonomics MD podcast

Starting a revolution is no easy task. Just ask Dr. Michael Stonebraker and Andy Palmer, co-founders of Tamr, the enterprise data mastering company. Their path to innovation begins with a universal problem. They also collaborate with other data radicals who challenge them to think differently and help them grow.Michael is a database pioneer, MIT professor, and entrepreneur. He has founded nine database startups over 40 years and won the A.M. Turing Award in 2014. Andy is a serial entrepreneur and founder, board member, and advisor for over 50 start-ups. Satyen, Michael, and Andy discuss Tamr's tech evolution, third normal form, and probabilistic methods.--------“There's a lot of work to be done in these big enterprises of getting all the data cataloged, getting it all mastered and curated, and then delivering it out for lots of people to consume. Early on at Tamr, we did a lot of stuff on-premise and those projects just took so much longer and you ended up doing a whole bunch of infrastructure stuff that's just not required. We're really encouraging all of our customers to think cloud native, multi-tenant infrastructure as the de facto starting point because that'll let them get to better outcomes much faster.” – Andy Palmer“Data products and data mastering are basically a cloud problem. And so you want to be cloud native, you want to run software as a service, you want to be friendly to the cloud vendors. Tamr spent a lot of time over the last two or three years doing exactly that. There's a big difference between running on the cloud and being cloud native and running software as a service. That's what we're focused on big time right now. After that, I think there's a lot of research directions we're paying attention to. Trying to build more semantics into tables to be able to leverage. You can think of this as leveraging more exhaustive catalogs to do our stuff better. I think that's something we're thinking about a bunch.” – Dr. Michael Stonebraker--------Timestamps:*(04:47): The procurement proliferation*(15:51): Solving data chaos*(24:49): Probabilistically solving data problems*(37:34): The future of Tamr*(43:16): A great technologist versus a great entrepreneur*(44:51): Satyen's Takeaways--------SponsorThis podcast is presented by Alation.Learn more:* Subscribe to the newsletter: https://www.alation.com/podcast/* Alation's LinkedIn Profile: https://www.linkedin.com/company/alation/* Satyen's LinkedIn Profile: https://www.linkedin.com/in/ssangani/--------LinksConnect with Andy on LinkedInConnect with Michael on LinkedInLearn more about DBOS

Over the last two seasons of Data Radicals, we've seen that data experts have been promoted to leadership roles. It's proof that organizations are seeing the value of data and the significance of establishing a data culture.In this episode, you'll hear from past guests like Stan McChrystal, Tricia Wang, and Paul Leonardi as they discuss traits of a successful data leader, adapting your data strategies, and the importance of soft skills.--------“I found that if I told somebody to do a task, they might try to do that task. But if I say, ‘Create this effect,' they owned it because they felt a level of responsibility for what approach that they chose, and it made it much stickier.” – Stan McChrystal, Retired US Army General“I think having gone through the valley of suffering myself, I have a massive amount of respect for founders because they carry a weight that most people will never realize. So it's hard for me not to like them.” – Jepson Taylor, Chief AI Strategist at Dataiku“Those CDOs that are most successful quickly establish trust within business, with business sponsors. They work with the business sponsors to identify what are the one or two or three most important things to them and see if they can solve those questions, even if it's with a very small subset of data, to begin to develop that relationship, that trust.” – Randy Bean, Author of Fail Fast, Learn Faster“You have to be able to have a learner's mindset. You have to understand what different teams and functions do and how they play into a bigger picture so that you can get into cause and effect. And then when you start to do that, you have a lot more ability to actually have impact.” – Wendy Turner-Williams, CDO at Tableau--------Time Stamps:*(00:48): Randy Bean: Alignment with expectations *(02:39): Jennifer Belissent: The diplomatic CDO*(05:01): Taylor Brown: Lead by example*(05:44): Ashish Thusoo: The DNA of a CDO*(07:48): Stan McChrystal: The strength of humility*(15:40): Paul Leonardi: Collaboration, computation, and change*(17:50): Mike Capone: Tapping your network*(18:39): Tricia Wang: The other vital “C's”*(19:41): Bernard Liautaud: Setting your North*(21:03): Jepson Taylor: Heroism and the human touch*(22:45): Wendy Turner-Williams: Leading future leaders--------SponsorThis podcast is presented by Alation.Learn more:* Subscribe to the newsletter: https://www.alation.com/podcast/* Alation's LinkedIn Profile: https://www.linkedin.com/company/alation/* Satyen's LinkedIn Profile: https://www.linkedin.com/in/ssangani/--------LinksListen to Randy Bean's episodeListen to Jennifer Belissent's episodeListen to Taylor Brown's episodeListen to Ashish Thusoo's episodeListen to Stan McChrystal's episodeListen to Paul Leonardi's episodeListen to Mike Capone's episodeListen to Tricia Wang's episodeListen to Bernard Liautaud's episodeListen to Jepson Taylor's episodeListen to Wendy Turner-Williams's episode

How does the NBA use data to compete and improve? When it comes to driving business growth with data, transparent communication makes success a slam dunk. By sharing innovative ideas and best practices across the business, one all-star team elevates the success of others across the entire organization.Michael James, SVP and Head of Data Strategy and Analytics at the NBA, is committed to creating a better fan experience and making better business decisions through collaboration. In this role, he bridges executive leadership and technical expertise to create a data-driven culture in constant pursuit of innovation. Satyen and Mike discuss the NBA's digital transformation, the future of GenAI in the league, and attracting more people to sports business analytics.--------“We have very active communication with our teams. You build up a relationship over time and you start to realize, ‘If this person is sharing this thing that worked, we have a good sense of who else might be able to benefit from it.' We'll make sure to package that up in a way that is not only informative, ‘Here's what the team did,' but also has the tangible next steps. ‘Here's what you can actually do with this to drive the business.' And it's no different on the data side. We've built a ton of data products through the years at the league level for our teams, also for different departments within our league office as well. But, the goal of all of those products is to make sure that we are driving better business decisions, we're driving a better fan experience, and, ultimately, that's going to lead to more revenue.” – Michael James--------Time Stamps:*(13:16): Sharing the (data) ball among the league*(17:34): Establishing best practices across an enterprise*(37:08): Measuring performance to measure culture*(41:16): Improving DEI in data*(46:57): Satyen's Takeaways--------SponsorThis podcast is presented by Alation.Learn more:* Subscribe to the newsletter: https://www.alation.com/podcast/* Alation's LinkedIn Profile: https://www.linkedin.com/company/alation/* Satyen's LinkedIn Profile: https://www.linkedin.com/in/ssangani/--------LinksFollow Michael on LinkedIn

As data radicals, we want to deliver insights that enable our organizations to know more, which we often do by providing an answer. Instead, we should be thinking about frameworks we can implement to communicate our ideas in simple and consumable ways.Dave Kellogg knows the importance of a framework. Dave is one of the leading enterprise executives in software today and currently serves as the Executive in Residence at Balderton Capital. His blog, Kellblog, is a highly regarded content hub for software leaders, drawing on his experience as an angel investor, board member, advisor, and thought leader. Satyen and Dave discuss the evolution of the data industry, problem solving with frameworks, and mapping your business in a complicated world.--------“People need the world simplified for them, and if you don't do it, somebody else will. A confused buyer is just going to buy from the market leader. If you're running a startup, you're definitionally not that. The burden of simplicity is on you. If you want to be successful, you need to have a very simple explanation of why someone should buy your stuff.” – Dave Kellogg--------Time Stamps:*(03:58): The evolution of BI and the BI customer*(22:25): Solving complex problems with simplifying frameworks*(32:41): Defining “data intelligence”*(43:16): The DNA of a D&A career*(47:44): Satyen's Takeaways--------SponsorThis podcast is presented by Alation.Learn more:* Subscribe to the newsletter: https://www.alation.com/podcast/* Alation's LinkedIn Profile: https://www.linkedin.com/company/alation/* Satyen's LinkedIn Profile: https://www.linkedin.com/in/ssangani/--------LinksFollow Dave on LinkedInFollow Dave on TwitterRead Dave's blog

If you're on a journey of fitness, you know that perfectionism is your enemy. The same goes for data. There will always be another achievement that you wish to reach. Instead, focus on creating habits that will lead you to better data decisions and long term health.Ameen Kazerouni knows this journey well. Ameen has spent his career at the intersection of science, data, and technology to create intuitive, data-driven experiences. In his role as CTO of Orangetheory Fitness, he is driving consumer wellness journeys by turning workout data into feedback and personalized recommendations. In this episode, Satyen and Ameen discuss data-driven exercise, keeping humans in the feedback loop, and AI data governance.--------“We make a lot of investment in demystifying the Orangetheory workout. And there's a lot of parallels to data, and I love that because when you think about data in an organization, ‘Well, it's going to be a multimillion dollar investment.' And it can get so overwhelming that instead of being like, ‘Let's start piece by piece,' the instinct becomes, ‘Let's just keep guessing instead.' Which is never a good idea. You should never, ‘Let's just revert to not using data at all because it's going to be really difficult to use data perfectly.' It's the same thing with fitness. You don't revert to doing nothing at all because meeting all the requirements will be hard. Showing up and getting started is what gets you going.” – Ameen Kazerouni--------Time Stamps:*(04:42): AI in the workout*(13:56): Data as a habit*(25:45): AI data governance*(38:36): The future of connected health*(44:08): Satyen's Takeaways--------SponsorThis podcast is presented by Alation.Learn more:* Subscribe to the newsletter: https://www.alation.com/podcast/* Alation's LinkedIn Profile: https://www.linkedin.com/company/alation/* Satyen's LinkedIn Profile: https://www.linkedin.com/in/ssangani/--------LinksFollow Ameen on LinkedIn

We've all heard the term “data literacy” by now. Although there is general consensus regarding the importance  of knowing how to read, write, and communicate with data, some folks may take issue with the term itself. Wendy Batchelder, CDO at Salesforce, wants to reframe the conversation and focus on how people can leverage data to do their jobs better.Wendy is a technology executive who has spent her career tackling business problems with technical solutions and transforming diverse team members into leaders. In her current role at Salesforce, Wendy is helping the right people access the right data at the right time — with the right controls. In this episode, Satyen and Wendy discuss the problems with data literacy training, the power of answering “so what?” questions, and the value of advocating for DEI in tech.--------“You have to drop the jargon and get down to what are you trying to explain? If you're trying to help people to use more data for decision making, then just introduce the data. Don't sit down and say, ‘We're gonna talk about data literacy,' because everyone's eyes gloss over and you lose their interest and their attention. It just doesn't give you a lot of respect. Part of our job as data experts is to help people to use data better and that's the conversation that should be had. But, the second you say things like data literacy, the tone of the conversation totally shifts.” – Wendy Batchelder--------Time Stamps:*(06:41): Data strategy at Salesforce*(26:37): Keeping up with connectivity*(28:40): Data literacy denial*(35:22): DE&I in data*(47:18): Satyen's Takeaways--------SponsorThis podcast is presented by Alation.Learn more:* Subscribe to the newsletter: https://www.alation.com/podcast/* Alation's LinkedIn Profile: https://www.linkedin.com/company/alation/* Satyen's LinkedIn Profile: https://www.linkedin.com/in/ssangani/--------LinksFollow Wendy on LinkedInRead Wendy's book Data Governance Handbook

Before search engines, we had to rely on memory and investigation to answer our questions. Then, search engines made answers instantly available. Now, in the age of AI, we have to engineer our questions to get the best results.Frank Farrall, Deloitte's Strategy & Analytics Ecosystems and Alliances Leader, knows that asking the right questions is just as critical as knowing the answers. Frank is a global business builder with 20 years of experience helping clients and startups become billion-dollar businesses through AI and digital transformation.In this episode, Satyen and Frank discuss identifying worthy investments, the sexiness of prompt engineering, and efficient engagement with AI.--------“I think in a lot of cases, prompt engineering will at least become a skill that knowledge workers, creative workers use to get an outcome from the technology. I think some people will be highly, highly specialized. I actually think prompts are going to have value in organizations and I think prompt libraries and how you manage prompts will become a set of IP and something that's highly valuable inside organizations. I think prompt engineering has a very significant future ahead of it. I think all of us are going to have to learn some level of prompt engineering to be effective in the future.” – Frank Farrall--------Time Stamps:*(02:42): Defining the AI ecosystem*(07:55): How to identify a worthy investment*(23:23): How “sexy” is prompt engineering?*(41:44): The future of generative AI*(44:43): Satyen's Takeaways--------SponsorThis podcast is presented by Alation.Learn more:* Subscribe to the newsletter: https://www.alation.com/podcast/* Alation's LinkedIn Profile: https://www.linkedin.com/company/alation/* Satyen's LinkedIn Profile: https://www.linkedin.com/in/ssangani/--------LinksFollow Frank on LinkedIn

As folks in the data space, we're introverts by nature. But, getting out of our comfort zone can open you up to endless possibilities. As one person who's gone from CIO to CEO can tell you, the key to growth is getting comfortable with feeling uncomfortable.That person is Mike Capone, CEO of Qlik, where he's revolutionizing the business intelligence landscape through data. In this episode, Mike shares with Satyen how his decades of experience in product development, data science, and go-to-market operations influence his role as CEO today. Satyen and Mike discuss transitioning from CIO to CEO, navigating economic downturns, and stepping out of your comfort zone.--------“Now is the time to get closer to your best customers. They're the ones who sustain you through these periods of economic ups and downs. The reality is for both of us and both of our companies, companies need data and analytics now more than ever. How are you going to navigate this uncertainty? You're going to navigate it through data. The conversation like, ‘Hey, we don't want to spend any more money on data and analytics because the environment is tough right now,' is actually counterintuitive. The reality is you need data and you need real-time data to get through it because your old data models are useless.” – Mike Capone--------Time Stamps:*(02:51): The growth of Qlik*(08:37): The relationship between private equity and software*(20:00): From CIO to CEO*(27:29): Navigating rough economic times with data and analytics*(33:10): Maintaining long-term landscape leadership*(40:24): Satyen's Takeaways--------SponsorThis podcast is presented by Alation.Learn more:* Subscribe to the newsletter: https://www.alation.com/podcast/* Alation's LinkedIn Profile: https://www.linkedin.com/company/alation/* Satyen's LinkedIn Profile: https://www.linkedin.com/in/ssangani/--------LinksFollow Mike on LinkedInFollow Mike on Twitter

As human beings, we're not accustomed to talking about data. In order to learn about new subjects, we traditionally use stories. However, bridging the gap between data and stories allows us to cross that barrier and create data-driven organizations.In this episode, Satyen interviews Ashish Thusoo, GM of AI and ML at AWS. Previously, Ashish was the Founder and CEO of Qubole, a pioneering cloud data lake platform. He also served Facebook as the Engineering Manager of Data Infrastructure where he co-created Apache Hive with the aim to democratize data access and analytics. Satyen and Ashish discuss the accelerated push to the cloud, building a data culture, and how the economic climate is impacting customers.--------“You have to remember, human beings are trained from the get-go to talk about stories, not data. That's how we learn. It takes special discipline to bring the conversation back to data, saying that, ‘You have this anecdote somewhere. Get me the data that proves or disproves it.' That specific mindset has got to be inserted in the organization, and that's how it becomes data-driven. It's a very fine line, but if you cross that line, essentially you become a data-driven organization. But, if you stay on the side of anecdotes and stories, then you can't bridge that.” – Ashish Thusoo--------Time Stamps:*(02:33): The SQL excitement that powered Hive *(13:42): The evolution of Qubole's founder hypothesis *(22:48): Navigating Amazon with AI/ML *(31:41): The future of AI/ML investment*(42:01): People are the foundation of the data culture*(45:57): Satyen's Takeaways--------SponsorThis podcast is presented by Alation.Learn more:* Subscribe to the newsletter: https://www.alation.com/podcast/* Alation's LinkedIn Profile: https://www.linkedin.com/company/alation/* Satyen's LinkedIn Profile: https://www.linkedin.com/in/ssangani/--------LinksFollow Ashish on LinkedInLearn more about AI/ML services on AWS

When building a data platform, it's important to stay true to your vision. Whether that's through creating a definitive user experience or an open platform that allows people to build upon it, you're constructing a cathedral. This cathedral is sophisticated and dependable, and allows for a bazaar of business intelligence, machine learning, and AI use cases.In this episode, Satyen interviews Matei Zaharia, Chief Technologist and Co-founder of Databricks. Matei is an open source trailblazer and the creator of Apache Spark, a widely used framework for distributed data processing. He is also an Associate Professor of Computer Science at Stanford University where he leads various data management and machine learning projects. Matei and Satyen discuss the Databricks and Alation partnership, exploring how platforms can help companies own their data, and consider the value of democratizing open source large language models.--------“One of the early stories about open source has been this thing about the cathedral and the bazaar. The cathedral is the thing that's all designed by one person, maybe. It's extremely coherent and so on, but also takes forever to build. And when you go there, there's one message you're hearing. And then the bazaar is the open thing. You don't know who's going to show up each day, but there'll be some really interesting goods and things that you just wouldn't see anywhere else. If you just want to get started and get stuff done, follow the defaults in the product and it'll work. But, we want to be open to some of that innovation and let people bring that in.” – Matei Zaharia--------Time Stamps:*(01:33): The story behind Spark*(11:56): Solving for user problems versus product vision*(20:12): The cathedral and the bazaar of open source*(24:04): Matei explains the Databricks Unity Catalog*(31:04): The Databricks and Alation partnership*(43:36): The data culture at Databricks*(48:21): Satyen's Takeaways--------SponsorThis podcast is presented by Alation.Learn more:* Subscribe to the newsletter: https://www.alation.com/podcast/* Alation's LinkedIn Profile: https://www.linkedin.com/company/alation/* Satyen's LinkedIn Profile: https://www.linkedin.com/in/ssangani/--------LinksFollow Matei on LinkedInFollow Matei on TwitterLearn more about Databricks's Unity CatalogLearn more about Alation + Databricks

Once considered the outcast of Silicon Valley, data has metamorphosed as a cool kid that everyone wants to be friends with. In the last decade, data has solidified itself as the key to success in business. The same shift can be said for India who primarily operated behind the scenes, has emerged as a leader in innovation.In this episode, Satyen sits down with Jitendra Putcha, EVP and Global Head of Data, Analytics, and AI at LTIMindtree. As an industry leader for over 20 years, he has solved data and analytics challenges for global companies by creating innovative next-generation solutions. Satyen and Jitendra discuss data platform modernization, data quality initiatives, and the future of AI and data science.--------“Gone are the days of looking at India as the back office and factory models, to looking at this is an opportunity. There are two, three reasons for it. One reason is about the startup ecosystem and the unicorns we started building, created aspirations for people and created curiosity for individuals even during school itself. Which wasn't the case a couple of decades back. That's one. The second is the promotion during school itself to encourage people to be driving incubation startups and throw their ideas has dramatically increased, there are many forums today. So, that's the second one. The third one, even the large SIs like us, today we have what we call entrepreneurs. Within our own ecosystem, people can come out with an idea, put an entire canvas and business plan, go to the board, get the funding, create that as an incubator, and go and test the market. If it is working, create that as an entire product line. I think when the young generation is able to get exposure, already been educated, and also they see in their workplace this kind of opportunity, I think that's the biggest benefit the younger generation is able to do, which probably wasn't the case before.” – Jitendra Putcha--------Time Stamps:*(09:57): The evolution of service providers*(13:22): The transformation of the Indian talent base*(30:52): The data marketplace and “data as a service”*(46:35): Defining the ROI of data tools*(53:17): Satyen's Takeaways--------SponsorThis podcast is presented by Alation.Learn more:* Subscribe to the newsletter: https://www.alation.com/podcast/* Alation's LinkedIn Profile: https://www.linkedin.com/company/alation/* Satyen's LinkedIn Profile: https://www.linkedin.com/in/ssangani/--------LinksFollow Jitendra on LinkedInFollow Jitendra on TwitterLearn more about Snowflake Summit

There are some things that just can't be quantified by data; imagine trying to portray your childhood in a spreadsheet! Yet these experiences are valuable. How can data teams capture qualitative information – and use it to steer the business? It starts with getting your data team out of the building. Only then can they gain insights about customer pain points and what the data is failing to tell us.In this episode, Satyen interviews Tricia Wang, a “tech ethnographer” and co-founder of Sudden Compass, a consulting firm helping companies improve their business through thick data. She also co-founded CRADL (Crypto Research and Design Lab) with the mission to create inclusive and sustainable growth of the crypto ecosystem. Satyen and Tricia discuss the power of thick data, the value of digital personhood, and the dangers of quantification bias.--------“Your job as a Chief Data Officer or a data leader in the company is, data is only part of your job generating the quantification to reflect back to the company. The other half is the bleeding edges around communication and helping the rest of your business, your business counterparts, to understand the value of this in a way that isn't scary and where they can see that it actually is going to improve their business. [...] But that takes a really brave kind of leader to work that way because it's not just about having the light shine on you, but it's about you making others and your company successful.” – Tricia Wang--------Time Stamps:*(01:35): The role of a tech ethnographer*(15:29): Tricia gives a rundown of thick data*(23:06): Understanding customers by getting out of the building*(32:36): Why quantification bias is dangerous to growth*(44:48): The importance of digital personhood*(57:22): Satyen's Takeaways--------SponsorThis podcast is presented by Alation.Learn more:* Subscribe to the newsletter: https://www.alation.com/podcast/* Alation's LinkedIn Profile: https://www.linkedin.com/company/alation/* Satyen's LinkedIn Profile: https://www.linkedin.com/in/ssangani/--------LinksFollow Tricia on LinkedInFollow Tricia on TwitterWatch Tricia's TED TalkVisit Tricia's websiteLearn more about Sudden Compass

In a world where technology is constantly evolving and AI is everywhere, it's all too easy for content to be deceitful, including scientific papers. Capturing source metadata, incentivizing reproducibility, and protecting whistleblowers are steps we can take to ensure science remains honest.In this episode, Satyen interviews Dr. Elisabeth Bik. Elisabeth is an experienced microbiologist whose groundbreaking work in scientific integrity has led to more than four thousand potential cases of improper research conduct. She also founded the blogs Microbiome Digest and Science Integrity Digest, and was awarded the John Maddox Prize for "outstanding work exposing widespread threats to research integrity in scientific papers" in 2021. Satyen and Elisabeth discuss image manipulation in scientific papers, the impact of AI on scientific integrity, and why paper mills must be stopped.--------“There's people looking at statistical problems or DNA sequences that don't make any sense, and appear to have been made up, or plagiarism. [...] We have a community of people doing this, data detectives or image detectives. And I think what we have in common is a desire to make science better and to flag these papers so that other people can see that there's a potential problem with that paper.” – Dr. Elisabeth Bik--------Time Stamps:*(01:34): Image manipulation in the context of scientific papers*(17:41): Elisabeth explains scientific paper mills*(22:52): Why biomedical research needs to slow down*(34:20): How Elisabeth manages backlash from scientists*(46:45): How prevalent fraud is in science today*(50:32): Satyen's Takeaways--------SponsorThis podcast is presented by Alation.Learn more:* Subscribe to the newsletter: https://www.alation.com/podcast/* Alation's LinkedIn Profile: https://www.linkedin.com/company/alation/* Satyen's LinkedIn Profile: https://www.linkedin.com/in/ssangani/--------LinksFollow Elisabeth on LinkedInFollow Elisabeth on TwitterVisit Microbiome DigestVisit Science Integrity Digest

Data governance is often seen as a confusing topic but everyone, even dummies, are capable of applying it to their organization. By starting with the “why” and acting on the most critical pieces, you can build a successful data governance initiative.In this episode, Satyen interviews Dr. Jonathan Reichental, author of Data Governance for Dummies and Founder of Human Future. He is an Adjunct Professor at several universities,  including the University of San Francisco, Pepperdine University, and Menlo College. Dr. Reichental also served as the Chief Information Officer at both O'Reilly Media and the city of Palo Alto, California. Satyen and Dr. Reichental discuss implementing data governance step-by-step, avoiding common governance pitfalls, and the future of smart cities.--------“I do think in the long run though, data governance is not about a narrow target. You will build a better business if you hire all the right people, if you build the right products, and deliver the right services, not by doing just one thing and doing it really well. It's a comprehensive approach to running a successful business, as you know well. And I think data governance should be thought of in the short term as targeting some very specific things, but long term as a cultural shift in how you actually think about data and how you use data on the backend and in the front end of your business.” – Dr. Jonathan Reichental--------Time Stamps:*(01:34): Dr. Reichental dives into his book Data Governance for Dummies*(08:51): How to convince people to invest in data*(13:27): Dr. Reichental defines data governance and how it relates to data management *(24:11): The signs a data culture is ready for governance*(42:42): Dr. Reichental's opinion on cryptocurrency and blockchain*(47:20): Satyen's Takeaways--------SponsorThis podcast is presented by Alation.Learn more:* Subscribe to the newsletter: https://www.alation.com/podcast/* Alation's LinkedIn Profile: https://www.linkedin.com/company/alation/* Satyen's LinkedIn Profile: https://www.linkedin.com/in/ssangani/--------LinksFollow Jonathan on LinkedInFollow Jonathan on TwitterRead Jonathan's book Data Governance for DummiesVisit Jonathan's website

Vulnerability is an important quality often overlooked in the world of tech. Yet being vulnerable and authentic helps you to set realistic expectations, speak with executives on a human level, and connect with your audience. In this episode, Satyen interviews Jepson (Ben) Taylor, Chief AI Strategist at Dataiku. Jepson is a visionary in the advancements of AI, ML, and data science. Prior to joining Dataiku, he served as the Chief AI Evangelist at DataRobot and co-founded the deep learning startup Zeff.ai, which was acquired by DataRobot in 2020. Jepson is a frequent industry speaker and collaborates with the data science community to improve AI and deep learning. Satyen and Jepson discuss the power of failure, the lie of job security, and proving data's worth through storytelling.--------"If nothing is failing, then it's not a very innovative company, not a very innovative culture. So there is a fraction of failure that for a mature organization you should celebrate. But with failure, you have the time urgency. How can we fail faster? I'd rather fail this week than four months from now." – Jepson Taylor--------Time Stamps:*(03:25): The special ingredient for speaking with executives*(11:52): Learning to embrace the expectation of failure and failing fast*(18:13): The two rules of good storytelling: authenticity and knowing your audience*(30:47): Jepson's advice for joining a startup and the lie of job security*(44:08): The importance of celebrating the soul of your user*(50:43): Satyen's Takeaways--------SponsorThis podcast is presented by Alation.Learn more:* Subscribe to the newsletter: https://www.alation.com/podcast/* Alation's LinkedIn Profile: https://www.linkedin.com/company/alation/* Satyen's LinkedIn Profile: https://www.linkedin.com/in/ssangani/--------LinksFollow Jepson on LinkedInFollow Jepson on Twitter

It's time to launch your digital transformation – but first you'll need new tools. Buyer, beware: Technology selection is tough because it's impossible to predict the future. How can leaders take this journey with clarity and confidence? In this episode, Satyen interviews professor Paul Leonardi, author of The Digital Mindset, to learn the answer. Paul is an expert in digital transformation and organizational change, Duca Family Professor of Technology Management at UC Santa Barbara, author of 4 books on technological innovation, and consults major tech companies like Google and Microsoft. Satyen sits down with Paul to discuss the skills leaders need to thrive in a digital landscape, how to demonstrate ROI with data, and why beta testing new software is critical for successful tech selection. --------“Many of our organizations today are not used to thinking about data as a byproduct of actions that we take on the suite of tools that we use to do our work. And a data culture, for me, is one that recognizes that almost everything we do produces data in some way, shape, or form. And we can use those data, maybe to our advantage, but at least we can use those data to explore, ‘Can they tell us things that we might not know or otherwise have access to, if we aren't perceptive and thinking about where those data exist and how we might use them?'” – Paul Leonardi--------Time Stamps*(01:47) How an organizational change expert views behavior and data*(15:04) The importance of beta testing technology's functionality*(18:04) Skills digital leaders need to thrive in the world of digital algorithms and AI*(22:17) Paul's inspiration behind authoring The Digital Mindset*(27:42) The 30% knowledge rule of surviving in a digital environment*(38:52) Paul breaks down what a digital mindset is*(46:11) How to successfully convince executives to invest in technology*(54:12) Satyen's Takeaways--------SponsorThis podcast is presented by Alation.Learn more:* Subscribe to the newsletter: https://www.alation.com/podcast/* Alation's LinkedIn Profile: https://www.linkedin.com/company/alation/* Satyen's LinkedIn Profile: https://www.linkedin.com/in/ssangani/--------LinksFollow Paul on LinkedInCheck out Paul's WebsiteRead Paul's book The Digital Mindset

Data has never been more readily available, yet the world seems more confusing than ever. In this episode, Satyen interviews Tim Harford, who's on a mission to help everyone become a Data Radical. As a Senior Columnist for The Financial Times, author of The Data Detective, and host of the Cautionary Tales podcast, Tim joins us ready to change how we view numbers—and in turn, the world. Him and Satyen discuss everything from how he develops ideas for stories driven by data to fostering a spirit of curiosity in how we approach the world (and try to change it). --------“Approach the world and numbers with a spirit of curiosity. Very often we don't behave like we like curiosity. We often like simple answers or we often like to just win an argument. But the world is a confusing place. The world is fascinating—I have questions and maybe the data can help me answer those questions. If that's the spirit with which you approach the data, then obstacles become intriguing. Mysteries become satisfying puzzles. Arguments turn into constructive, exploratory questions and it's just a lot more fun.” - Tim Harford--------Time Stamps* (2:26) How an award-winning storyteller approaches his work* (8:13) Data brings people comfort and knowledge in times of crisis (like the pandemic)* (16:50) A glimpse into Tim's book The Data Detective* (19:49) The importance of “the stuff around numbers” in increasing data literacy* (25:03) Approaching the world with humility and curiosity* (37:15) How you can be an undercover economist* (39:10) Satyen's Takeaways --------SponsorThis podcast episode is presented by Experian.Learn more:* Subscribe to the newsletter: https://www.alation.com/podcast/* Alation's LinkedIn Profile: https://www.linkedin.com/company/alation/* Satyen's LinkedIn Profile: https://www.linkedin.com/in/ssangani/--------LinksFollow Tim on LinkedInCheck out Tim's Podcast Cautionary TalesRead Tim's Book “The Data Detective”

The second season of the Data Radicals podcast launches on February 15th! I'm your host, Satyen Sangani.In TV, some second seasons can be disappointing. After a triumphant season one, there's no more story to tell.Fortunately, that's not the case in tech. Innovations, discoveries, and market movement — plus a new round of guest stars — guarantee plenty of plots and intrigue, all with one common theme: data.Last season, we heard from industry leaders, journalists, analysts, and founders. They gave expert advice for using data to navigate any struggle: from overhauling your company's governance strategy… to even getting a date!These data radicals see things that nobody else can. And this next season is no different. We have incredible guests lined up who will give you the tools you need to bring your business – and career – to the next level. We're welcoming guests like: Tim Harford, of the BBC's More or Less; Jonathan Reichental, Author of Data Governance for Dummies; Mike Capone, CEO of Qlik (and Talend), Ameen Kazerouni, CTO of OrangeTheory, and so many more.So tap the follow button and get ready to hear radical strategies from the most innovative minds in the world.Welcome to season two of Data Radicals!Powered by the team at Alation. 

Data governance isn't easy. It demands a vision, strategy, and clear-cut plan that ultimately supports the business. Many have tried, and failed, to lead governance initiatives. What can we learn from the rare few who have led these tricky projects to success?Learn top tips in this supercut episode, which compiles the best data governance advice from season 1. Featuring Bob Seiner of KIK Consulting, Jennifer Belissent, Principal Data Strategist at Snowflake, Francesco Marzoni, CDO of Inkga Group, Michelle Hoiseth, former CDO of Parexel, and more!--------“We were, very much, very careful about using language around data enablement, not data governance. Yes, there's a certain amount of this, of course, that's about control. But it's control and service to the aims of the business. It's not a gate control for the sake of pure defensive posture. As a business, we needed to be able to do more with our data. It's been an educational journey and it had to be timed with the advanced analytics initiatives.” - Michelle Hoiseth, former CDO of Parexel--------Time Stamps* (1:12) What is Data Governance?* (4:38) How to get stakeholders excited about governance* (7:10) Making your implementation a success--------SponsorThis podcast is presented by Alation.Learn more:* Data Radicals: https://www.alation.com/podcast/* Alation's LinkedIn Profile: https://www.linkedin.com/company/alation/* Satyen's LinkedIn Profile: https://www.linkedin.com/in/ssangani/--------Links* Connect with guest Bob Seiner on LinkedIn* Connect with guest Paola Saibene on LinkedIn* Follow guest Francesco Marzoni on LinkedIn* Follow guest Jennifer Belissent on LinkedIn* Follow guest Wendy Turner-Williams on LinkedIn

The modern data stack, sparked by the Redshift revolution and furthered by cloud-platform players like Snowflake and Databricks, forever changed the data integration landscape. Realizing that ETL tools badly underperformed in the cloud, Fivetran strengthened the stack with an ELT pipeline to perform transformations within the data warehouse environment. George Fraser, Fivetran Co-Founder and CEO, and Taylor Brown, Fivetran Co-Founder and COO, join us in this episode to discuss their founding story — from Y Combinator to $5.6 billion valuation — and the hard reality that data's role is often to prove your assumptions are wrong.--------“Taylor was the one who really locked onto this term years ago. I remember him saying ‘modern data stack, that's what we're doing.' And it was not a commonly used term at the time. He's like, ‘that's the term we need to lock onto.' Over the years it has really grown, but he has a decent amount to do with the present day popularity of that term.” — George Fraser--------Time Stamps* (0:00) A deep dive into Fivetran* (10:10) Navigating the product journey* (15:02) Normalization vs denormalization* (17:00) The power of saying “no”* (20:15) Inventing the Modern Data Stack* (27:26) The future of Fivetran* (29:47) Making data-driven decisions* (33:20) Advice for building your own data culture--------SponsorThis podcast is presented by Alation.Hear more radical perspectives on leading data culture at Alation.com/podcast--------LinksConnect with George on LinkedInConnect with Taylor on LinkedInCheck out Fivetran

DataOps is having a moment. Where does it sit in the data lifecycle? And how is this emerging trend changing data management today? To find out, Satyen sits down with guest speaker Michele Goetz, author of The Forrester Wave: Enterprise Data Catalogs for DataOps.--------“DataOps is really the engineering and practices of designing and developing data capabilities, launching them out to production and ensuring that they're providing value and delivering on the outcomes that businesses expect in being able to use that data.” — Guest Speaker Michele Goetz--------Time Stamps* (0:00) The birth of DataOps* (2:43) What is DataOps?* (11:18) DataOps and the Data Mesh* (18:41) Diving into data prep* (22:09) Tackling data governance for your data catalog* (31:17) The future of the data cataloging landscape--------SponsorThis podcast is presented by Alation.Hear more radical perspectives on leading data culture at Alation.com/podcast--------LinksConnect with guest speaker Michele on LinkedInCheck out Forrester

Librarians have played a crucial role in the management of data throughout history. From the halls of the Library of Alexandria to the Library of Congress all the way to your elementary school: librarians have been the guardians of our knowledge for thousands of years. But now that we're in the digital age…has that role shifted? That's what we're exploring today.Deb Seys, Senior Director of Learning and Communities at Alation, is a passionate librarian who has made the jump from the dewey decimal system to the data catalogue. She shares with us how data is the most powerful tool in a librarian's arsenal, how data can better your user experience, the steps to finding the best answers for any question, and much more. --------"One of the most misunderstood things about data is that it's this objective hard thing that sits there and reveals something. It's just not true at all. A lot of the work of documenting metrics is about what's important to a group of people, and then using that to tell a story or make a decision." - Deb Seys--------Time Stamps* (0:00) How librarians have championed data for millennia * (4:25) The modern-day librarian's biggest ally is the data catalogue * (8:24) Understanding the basics of data* (14:45) How to be a data-driven librarian* (17:09) The relationship between data and user experience at eBay* (22:04) The secret to finding the right answers* (26:52) Creating the right data mindset--------SponsorThis podcast is presented by Alation.Hear more radical perspectives on leading data culture at Alation.com/podcast--------LinksConnect with Deb on LinkedInCheck out Alation

In this episode, CDO Steve Pimblett of The Very Group describes the four pillars of extracting value from data and shares how he's built a successful B2C data team. Steve shares his advice for CDOs just starting off or maybe years into the role. He discusses optimizing your data strategy, making your business more data-driven, leveraging account managers, and much more.--------“Set up some sort of an internal agency to see how you can make business areas more data-driven.” - Steve Pimblett--------Time Stamps* (2:28) What CDOs should know on day one* (8:44) A deep dive into The Very Group* (14:26) How to approach your company's data strategy* (20:56) Using data to better approach tough conversations* (22:59) Account managers are your secret weapon--------SponsorThis podcast is presented by Alation.Hear more radical perspectives on leading data culture at Alation.com/podcast--------LinksConnect with Steve on LinkedInCheck out The Very Group

With the data space more complex than ever, many people throw their hands in the air, and use solutions that fix many (but not all) of their problems. Today's guest saw that complexity, and leaned into it. Zhamak Dehghani is the creator of the data mesh. Where others saw chaos, she saw an opportunity. Zhamak dives into decentralization, all things data mesh, how data architecture can empower your workers, and much more.--------“Seeing the real world problems made me curious about the data space—scratching the surface and seeing the discord between the reality of the complex world we're living in with data. The solutions weren't up to the task for dealing with that complexity, so it got me to look further for a solution.” — Zhamak Dehghani--------Time Stamps* (0:00) A brief history of data architecture* (2:45) An intro to the data mesh* (13:08) How analytics impact data engineers* (18:54) The socio-technical approach* (23:26) Getting started in the data mesh* (28:59) Data mesh vs. Data fabric--------SponsorThis podcast is presented by Alation.Hear more radical perspectives on leading data culture at Alation.com/podcast--------LinksConnect with Zhamak on LinkedInCheck out Zhamak's book Data Mesh

What if you could combine data across industries and use cases? FAIR data is Findable, Accessible, Interoperable, and Reusable. These are the tenants that Francesco Marzoni, Chief Data and Analytics Officer of Ingka Group, has made central to his data-driven career. In today's episode, Francesco discusses the FAIR principles, data silos, the importance of data governance, and much more.--------“The biggest lesson I got during the pandemic was the importance of having usability in data assets you can tap into and how much it can hurt you if you don't have usable data assets in times of crisis.” — Francesco Marzoni--------Time Stamps* (0:00) How Aristotle impacts data today* (2:45) Exploring FAIR* (14:07) Francesco used FAIR to navigate Nestlé through the pandemic* (20:52) The reusability of data* (27:00) How Francesco creates data programs* (29:54) Future opportunities in data--------SponsorThis podcast is presented by Alation.Hear more radical perspectives on leading data culture at Alation.com/podcast--------LinksConnect with Francesco on LinkedInCheck out Ingka Group

While analysts in other fields face an ocean of data, those in social justice often face a desert. After all, those who abuse their power take care to conceal their crimes. How can data scientists hold the guilty accountable? Today's guest has used data to uncover hidden human rights violations and uphold social justice. Tarak Shah is a Data Scientist at the Human Rights Data Analysis Group (HRDAG), a RAFTO award-winning non-profit. In this episode, he reveals how his work has exposed the crimes of violent dictators and police – delivering justice to the violated and a chance to heal the communities affected. --------“In human rights, the question when we're talking about accountability is about what actually happened, not just what was documented.” — Tarak Shah--------Time Stamps* (0:00) Navigating a lack of data* (2:46) Analyzing human rights violations in Guatemala * (11:45) How data solved a murder mystery* (14:02) Data's insights into gender-based violence in Chicago* (34:33) How you can help preserve human rights with data--------SponsorThis podcast is presented by Alation.Hear more radical perspectives on leading data culture at Alation.com/podcast--------LinksConnect with Tarak on LinkedInCheck Out HRDAG

In the era of “fake news” how do you know what to trust? Today's guest, Seth Stephens-Davidowitz, has found the last dependable source of truth: Google. Armed with Google trends data, Seth illuminates hidden truths about racism, politics, and sexuality in our world today. In today's interview, Seth dives into his latest book Don't Trust Your Gut: Using Data to Get What You Really Want in Life. He shares interesting insights he gathered along the way and how unfortunately, lying and data sometimes go hand-in-hand.--------“Google trends is so powerful because it gives you an incentive to get the information you need. And PornHub, similarly, gives you an incentive to get the information you need. So even in an anonymous survey, there's no incentive for people to tell the truth.” — Seth Stephens-Davidowitz--------Time Stamps* (0:00) Is your data full of lies?* (2:45) Seth's book Everybody Lies* (6:25) Google trends is a data treasure trove* (11:36) How data can help you online date* (16:25) Taking a data-driven approach to your personal life* (19:33) The data behind happiness * (24:13) Seth's book Don't Trust Your Gut and how it can change your approach to business--------SponsorThis podcast is presented by Alation.Hear more radical perspectives on leading data culture at Alation.com/podcast--------LinksCheck out Seth's WorkSeth's book : Don't Trust Your Gut: Using Data to Get What You Really Want in Life

Business intelligence has dominated corporate conversations for years. It's an integral component of making data-backed decisions and as well as an important tool for any Data Radical. Today, we're lucky enough to speak with a business intelligence pioneer, Bernard Liautaud.Bernard is the Managing Partner of Balderton Capital and was the founder of BusinessObjects. In this interview, he and Satyen discuss the origins of business intelligence, what it's like to found a company, creating healthy company cultures, and so much more.--------“The No. 1 element of creating a culture is by setting an example, because you're going to be modeled after — unconsciously or consciously.” — Bernard Liautaud--------Time Stamps* (0:00) Bernard's impressive history of making data digestible * (2:45) The history of BusinessObjects* (5:10) Inventing a new way to look at data* (11:39) A deep dive into spearheading business intelligence* (30:40) Creating a unique corporate culture--------SponsorThis podcast is presented by Alation.Hear more radical perspectives on leading data culture at Alation.com/podcast--------LinksConnect with Bernard on LinkedInCheck out Balderton Capital

Knowledge graphs are a critical tool in a Data Radical's toolbox. But how can we make sure we're leveraging them to the best of our ability? Today's guest helps us out.Kendall Clark, is the Founder and CEO of Stardog. His non-typical data journey has given him a wealth of knowledge that we're lucky enough to hear today. He goes deep into knowledge graphs, philosophy's impact on management, and much more.--------“It's a little bit like asking the first person you ever date to marry you. It's not that that's definitely a mistake and we'll never work out, but it's risky. This is really what happens when you commit to doing integrations in the storage layer.” - Kendall Clark--------Time Stamps* (0:38) The human impact on data* (3:06) Kendall's unconventional journey into data* (6:27) What is Stardog?* (8:52) All you need to know about Knowledge Graphs* (27:20) How to build culture at your organization--------SponsorThis podcast is presented by Alation.Hear more radical perspectives on leading data culture at Alation.com/podcast--------LinksConnect with Kendall on LinkedInCheck out Stardog

Information is power, and data is rarely as subjective as it seems. Savvy data leaders know one thing: data is political. And for many data professionals — that fact can feel discouraging. But it doesn't have to be.Today, Wendy Turner-Williams, CDO of Tableau, brings us a fresh perspective on how to win at the game of data politics. Shifting corporate culture can be difficult. But with Wendy's tips and tricks, you'll be able to transform your org into a data-driven machine. You won't want to miss it.--------Quote:“When it comes to culture the thing that data professionals never love to talk about is that data's very political.” - Wendy Turner-Williams--------Time Stamps* (00:24) Who is Wendy Turner-Williams* (2:37) Ins and outs of working on data in a software company* (7:17) CDOs as supporting actors* (16:26) The evolution of data governance* (22:13) Wendy's approach to data culture* (24:45) The politics of data--------SponsorThis podcast is presented by Alation.Hear more radical perspectives on leading data culture at Alation.com/podcast--------LinksConnect with Wendy on LinkedInCheck out Tableau

Data is one of our most underutilized weapons in our arsenal. In today's battles, the ability to gather, disseminate, consume and act on information has become the fundamental capability in the war on terror.In this episode, Satyen speaks with Stan McChrystal, retired US Army General and Managing Partner of the McChrystal Group. They discuss Stan's experiences building a data culture in the US military, evaluating leaders, the concept of empowered command, and much more.--------“Often you have data you don't know you have. ” - Stan McChrystal--------Time Stamps* (0:00) Using data as a weapon* (3:16) Insight into changing massive organizations * (11:33) How to find the best leaders* (18:17) Running military operations backed by data* (29:37) What success looks like for a US Army general--------SponsorThis podcast is presented by Alation.Hear more radical perspectives on leading data culture at Alation.com/podcast--------LinksConnect with Stan on LinkedInCheck out the McChrystal Group

The role of CDO is constantly evolving, and Data Radicals need to stay ahead of the curve. Today's guest gives us the inside scoop on how to do just that. Randy Bean is the founder and CEO of NewVantage Partners and author of Fail Fast, Learn Faster: Lessons in Data-Driven Leadership in an Age of Disruption, Big Data, and AI. In this interview, he and Satyen discuss the adoption of the chief data officer role, the challenges of creating a data culture, and the importance of soft skills for CDOs. --------“Data-driven organizations never rest. They're never comfortable. Because they know that unless they continue to do things to stay data-driven—they won't be the most data-driven going forward.” - Randy Bean--------Time Stamps* (0:00) How the Dunning-Kruger effect impacts your organization* (3:10) Randy's beginnings in data* (6:31) The endless data journey* (10:05) The evolution of the CDO* (19:51) How to know you're a successful CDO* (23:54) Barriers to building a data culture--------SponsorThis podcast is presented by Alation.Hear more radical perspectives on leading data culture at Alation.com/podcast--------LinksConnect with Randy on LinkedInCheck out NewVantage PartnersRead Randy's Book: Fail Fast, Learn Faster: Lessons in Data-Driven Leadership in an Age of Disruption, Big Data, and AI

The early founders of the internet argued that privacy was dead. But today's guest was motivated to revolutionize data privacy instead. Michelle Finneran Dennedy, CEO of PrivacyCode and co-author of The Privacy Engineer's Manifesto, is one of the world's first Chief Privacy Officer. She and Satyen talk about how the role of CPO has changed throughout her tenure, the tough work of designing privacy policies, the future of data privacy, and much more.--------“CPOs today are business leaders and risk takers.” — Michelle Finneran Dennedy--------Time Stamps* (0:00) Privacy is dead. Get over it.* (5:54) What made Michelle passionate about privacy* (10:05) The evolution of the Chief Privacy Officer* (12:29) What is data policy?* (14:26) The roles morals and ethics play in data policy* (19:23) Debunking privacy engineering* (29:11) The future of privacy--------SponsorThis podcast is presented by Alation.Hear more radical perspectives on leading data culture at Alation.com/podcast--------LinksConnect with Michelle on LinkedInCheck out The Privacy Engineer's Manifesto

No risk, no reward. Kyle Kirwan, co-founder and CEO of BigEye, helps companies manage risk more intelligently through the power of data quality. In this interview, Kyle describes his experience as one of the first data scientists and analysts at Uber, weighs the pros and cons of build versus buy, and defines the modern data stack – with an eye to what's next. --------“We're living in this Renaissance era when it comes to data tools.” - Kyle Kirwan--------Time Stamps* (0:00) What Monopoly teaches us about data* (3:00) Data's role at Uber* (7:29) Building vs. Buying* (12:14) The current and future landscape of data tools* (17:58) Getting the right people involved* (20:20) Creating a data culture* (28:48) Insights into the modern data stack--------SponsorThis podcast is presented by Alation.Hear more radical perspectives on leading data culture at Alation.com/podcast--------LinksConnect with Kyle on LinkedInCheck out BigeyeSeven Principles for Reliable Data Pipelines by Kyle KirwanRegister for the Data Reliability Engineering ConferenceData Discovery in 2020 by Kyle Kirwan

Science and data are powerful tools of discovery, but our expectations are often misaligned with what science can actually do. Interpreting and understanding science involves nuance, humility, and an open mind – muscles that we don't always flex as often as we should.Today's guest is Christie Aschwanden, journalist and NYT bestselling author. Christie is an expert in understanding the power – and limitations – of science. Christie explains why science isn't broken, how to get reliable answers from the scientific method, and the science behind why quitting can sometimes be the best decision possible.--------“I think it's really important to always recognize that there's a possibility that whatever you're thinking now is wrong…We need to understand that one of the most fundamental aspects of science is that it's provisional. We always have to be open to new evidence and recognize that there's always the chance that we will gain new evidence that will overturn our current ways of thinking. And that's okay.” -Christie Aschwanden--------Time Stamps* (3:12) Is Science Broken?* (7:07) What is Motivational Reasoning?* (11:27) The Importance of Nuance in Science * (12:50) One Trait Christie Highly Recommends * (14:40) The Misaligned Incentive Structure in Science Today* (16:38) Stories Are the Way We Make Sense of Data* (19:44) The Creative Process and the Value of Quitting* (23:35) The #1 Thing that Any High-Performance Person Can Do* (25:40) The Importance of Not Being Productive* (27:21) The Benefits of Sleep and How to Get Better Sleep* (30:30) Christie's #1 Piece of Advice--------SponsorThis podcast is presented by Alation.Hear more radical perspectives on leading data culture at Alation.com/podcast--------Links* Christie's Website* Good To Go: What the Athlete in All of Us Can Learn from the Strange Science of Recovery* Follow Christie on Twitter* Christie's Podcast “Emerging Form”* Christie's FiveThirtyEight Archive* Psychology's Replication Crisis Has Made The Field Better from FiveThirtyEight

The average CDO only lasts 18 months in their position. 18 months! With odds that dire, data leaders need all the inside scoop they can get to climb the massive mountain ahead of them. Luckily, today we're giving you a roadmap.Today's guest is Peter Jackson, Co-Founder and Director of Caruthers and Jackson. Peter shares his advice on how to up your odds of passing that 18-month mark with flying colors. He discusses why CDOs are key players in a company's future, and offers tips for navigating vendor relationships, building up data literacy in your organization, and much more.--------"Wherever you find a spreadsheet—that's an opportunity for a quick win, because you might be able to automate that process by using some technologies and by teaching people new skills, and that will reduce data errors.” - Peter Jackson--------Time Stamps* (0:00) The high stakes for CDOs* (2:29) How CDOs are change agents* (6:02) How to know if being a CDO is right for you* (8:40) Advice for new CDOs* (11:45) The secrets of spreadsheets* (17:06) How to make the most of vendor relationships* (23:48) Building data literacy at your organization--------SponsorThis podcast is presented by Alation.Hear more radical perspectives on leading data culture at Alation.com/podcast--------LinksConnect with Peter on LinkedInCheck out Carruthers and Jackson

Whether you're a whistleblower exposing fraud or a new CDO with uncomfortable insights at an organization, “just the facts” alone won't convince the crowd. You need buy-in, conviction, and the ability to tell a compelling story.In today's episode, Dr. Margaret Heffernan, author, professor, and seasoned CEO, shares what she's learned about leading teams to light. She shares insights on willful blindness, how to make people care about data, and how to build the most productive teams. --------"What's really interesting about whistleblowers is that they're deeply ordinary." - Dr. Margaret Heffernan--------Time Stamps* (0:03) A history of whistleblowers* (2:43) Alice Stewart and a pattern of willful blindness to important data* (9:38) Data alone doesn't win arguments* (19:59) The psychology of whistleblowers * (27:31) How to be a whistleblower* (30:00) The downside of being a super chicken--------SponsorThis podcast is presented by Alation.Hear more radical perspectives on leading data culture at Alation.com/podcast--------LinksConnect with Margaret on LinkedInCheck out Margaret's book Uncharted: How to Map the Future

What can the tale of the blind men and the elephant teach us about our own blindspots in the world of data?Today's guest helps us identify some of our data blindspots and learn how to attack them head on. Cindi Howson, Chief Data Strategy Officer at ThoughtSpot, shares how BI has transformed in recent years, what you can do to increase data literacy at your org, how your company can stay ahead of the hiring curve, and much more.--------"CDOs have to associate with others outside the organization so they do not get demotivated or burned out when there's too many setbacks or naysayers." - Cindi Howson--------Time Stamps* (0:00) What elephants teach us about data* (4:00) BI: then and now* (12:05) The urgency of increasing digital literacy* (17:07) How to start your data transformation* (19:42) Competing in the labor market* (26:49) The Data Chief Podcast--------SponsorThis podcast is presented by Alation.Hear more radical perspectives on leading data culture at Alation.com/podcast--------LinksConnect with Cindi on LinkedInCheck out ThoughtSpot

Corporate malfeasance is a cold fact. And when companies lie to the public, real people get hurt.Amir Efrati, Co-Founder and Executive Editor of the Information, exposes the truths big firms conceal. His reporting has brought corporations to justice, won numerous awards, and been cited by federal judges. In this episode, Amir discusses the Facebook Papers, controversies around self-driving cars, and the relationship between data-driven decisions and transparency. This one isn't for the faint of heart, and you won't want to miss it.--------"There was this dissonance between what was privately being shared and what was publicly being announced. People are making life decisions based on completely false assumptions. That's not good for anyone. Investors are investing pension money and other people's money in companies based on what's publicly announced and not what's privately known. That's not good either." - Amir Efrati--------Time Stamps* (0:00) Corporate responsibility vs public good* (3:18) What's The Information?* (6:31) The inside scoop on the Facebook Papers* (14:51) How to hack humans* (17:12) The secrets of self-driving cars* (23:57) Why the cloud is a trillion dollar industry--------SponsorThis podcast is presented by Alation.Hear more radical perspectives on leading data culture at Alation.com/podcast--------LinksConnect with Amir on LinkedInCheck out The Information

The world of data is often elusive and nebulous. And as time goes on, different myths circulate the zeitgeist. Today's guest walks us through some common myths, and serves as our own personal mythbuster. Michelle Hoiseth, Chief Data Officer of Parexel, uncovers the biggest data challenges facing the pharmaceutical industry, and shares how you too can be a data mythbuster, how you can lead a data journey at your organization, and much more. --------“I use a cartoon still where the top frame is ‘who wants clean data' and everybody in the crowd has their hand up. Then the next frame is ‘who wants to clean their data' and everyone's hand is down and they're looking at their shoes—and that was Parexel." - Michelle Hoiseth--------Time Stamps* (0:00) Being a data mythbuster * (2:45) The data problems facing the pharmaceutical industry* (10:42) Embarking on a data journey* (24:10) Lessons learned from a data overhaul* (25:23) A data cultural evolution--------SponsorThis podcast is presented by Alation.Hear more radical perspectives on leading data culture at Alation.com/podcast--------LinksConnect with Michelle on LinkedInCheck out Parexel

Anxiety about math. For most Americans, it's so deeply ingrained it's practically a personality trait. Unfortunately, this fear can linger in our psyches as we age. But, thankfully, Data Radicals like Caroline Carruthers are here to confront that fear and educate our data-anxious peers.Caroline is the co-author of “The Chief Data Officer's Playbook,” and today she's explaining why CDOs play a crucial role in building a data-based organization. She shares advice on how to be an effective CDO, and promote data literacy so people embrace data-driven decision making at your company, and much more.--------"Spend time with your stakeholders and talk to them about data. Relax them, take them out for coffee and cake, sit there and just get to know them as a person and ask them about what they're trying to do." - Caroline Carruthers--------Time Stamps* (0:04) Being a data cheerleader* (2:39) How to be an effective CDO* (8:45) Finding your data skillset * (11:59) Turning your stakeholders into Data Radicals* (14:40) Teaching data literacy to your organization* (20:18) Raising the next generation of Data Radicals* (26:23) Meeting people where they are--------SponsorThis podcast is presented by Alation.Hear more radical perspectives on leading data culture at Alation.com/podcast--------LinksConnect with Caroline on LinkedInCheck out Carruthers and Jackson