The Data Standard

In this episode, guest Prashant Natarajan sits down with TDS to discuss this new book and applications in AI as well as data advice. Prashant Natarajan is the Vice President of H20.ai Health and Life Sciences division with a record of turning things around at Siemens Oracle Deloitte Unum. He is a Co-Faculty Instructor at Stanford University, author of numerous best-selling books e.g. “Demystifying Big Data & Machine Learning for Healthcare,” published by Taylor & Francis. His latest book is on its way " Demystifying Artificial Intelligence for the Enterprise: Building Tomorrow's Self-Driving Organization (upcoming 2021)". Connect with Prashant on LinkedIn  The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration. https://datastandard.io  https://www.linkedin.com/company/the-data-standard  https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q 

In this episode, we talk with Sam Anthony, the CTO, and co-founder of Perceptive Automata, a company that makes software to help autonomous vehicles understand human behavior. We discuss the missing piece for autonomous driving, why it is such a hard problem for autonomous vehicles to understand human intention and behavior, safety standards and testing for autonomous vehicles, Perceptive Automata's business, how Perceptive Automata's software works in ADAS and AV systems, how the algorithms are trained, and the state of autonomous vehicle development. Connect with Sam on LinkedIn  The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration. https://datastandard.io https://www.linkedin.com/company/the-data-standard https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

Mickey Alon is a serial entrepreneur, passionate about designing, building, and launching innovative products that drive business outcomes. He's Co-author of Mastering Product experience in Saas and CPO. Currently, he's the CTO and Founder of Gainsight PX, a leading Product-growth platform. In this episode, guest Mickey Alon sits down with TDS to discuss Using data for marketing automation. Connect with Mickey on LinkedIn  The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration. https://datastandard.io https://www.linkedin.com/company/the-data-standard https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

 Ihsan Saracgil, Principal Data Scientist at Visible Alpha sits down with TDS to advise Ph.D. students in investment research.  Connect with Ihsan on LinkedIn  The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration. https://datastandard.io https://www.linkedin.com/company/the-data-standard https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

Data science is an interdisciplinary field that extracts knowledge and insights from many structural and unstructured data, using scientific methods, data mining techniques, machine-learning algorithms, and big data. The healthcare industry generates large datasets of useful information on patient demography, treatment plans, results of medical examinations, insurance, etc. Data science provides aid to process, manage, analyze, and assimilate the large quantities of fragmented, structured, and unstructured data created by healthcare systems. This data requires effective management and analysis to acquire factual results. In this episode, guest Jonah Leshin sits down with TDS to discuss the importance of making data useable in healthcare. Jonah joined Datavant from Highland Math, where he was co-founder and Chief Data Scientist, leading data analytics and data monetization. Jonah holds a Masters in Math from the University of Cambridge, where he studied as a UK Fulbright Scholar, and a Ph.D. in Math from Brown University. Outside of work, Jonah enjoys playing tennis and taking family walks. Connect with Jonah on LinkedIn  The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration. https://datastandard.io https://www.linkedin.com/company/the-data-standard https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q 

Antony Akisetty, Data Scientist & Global Search Strategist at Accuride International sits down with TDS to discuss their journey in the data science field and applications within small median manufacturing. Connect with Antony on LinkedIn  The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration. https://datastandard.io https://www.linkedin.com/company/the-data-standard https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

In this episode, guest Bilal Clarence sits down with TDS to discuss Data Privacy. Bilal is currently working at Capital One as Senior Director of Privacy and Data Solutions. Clarance was a member of the Pioneer men's basketball team from 2001-2003 and the Bearcat men's basketball team from 2003 to 2005, including the 2003-'04 squad that advanced to the NCAA Division II Elite Eight and was inducted into Northwest's M-Club Hall of Fame in 2014. Continuing his basketball career after college, Clarance played basketball in Europe from 2005-2009. He was a member of the Danish men's national team and served as captain from 2007 to 2009. Connect with Bilal on LinkedIn  The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration. https://datastandard.io https://www.linkedin.com/company/the-data-standard https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

In this episode, guest Jose Unpingco sits down with TDS to discuss Data sensitivity and defects as well as defining a health data paradox. Dr. Jose Unpingco is currently the Senior Director for Data Science/Machine Learning at West Health Institute in La Jolla, a nonprofit medical research organization. Dr. Unpingco earned his Ph.D. in 1997 from the Electrical and Computer Engineering Department at the University of California, San Diego. Prior to joining West Health, Dr. Unpingco worked with the SSC Pacific High-Performance Computing Center as an on-site Director for the DoD High-Performance Computing Modernization Program (HPCMP) in the PETTT component of HPCMP where he helped develop large scale file transfer technology that is still used today, as well as encouraging the DoD to adopt open-source technology such as Python for scientific computing.In addition to his work at SSC Pacific, Dr. Unpingco has extensive industrial experience as a research engineer and technical director at Hughes Aircraft Co., Raytheon, Mission Research, and ATK, working on a wide range of systems -- underwater acoustics, adaptive antennas, radar detection, and imaging, and modern target tracking. Dr. Unpingco is the author of two internationally published books by Springer titled “Python for Signal Processing” and “Python for Probability, Statistics and Machine Learning.” In addition to his duties at West Health, Dr. Unpingco is an invited lecturer at UCSD, teaching undergraduate/graduate Data Science classes. He also sits on the industry advisory council for UCSD Extension's Data Science and Machine Learning program. Connect with Jose on LinkedIn  The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration. https://datastandard.io https://www.linkedin.com/company/the-data-standard https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

In this episode, guest Nelson Tsaku sits down with TDS to discuss tips for business in data literacy and a crisp data model. Connect with Nelson on LinkedIn   The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration. https://datastandard.io https://www.linkedin.com/company/the-data-standard https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

Milan Patel, Global Director, Data Science at ADARA, sits down with TDS to discuss analytical products that produce factual insights through low-cost high-value processes. Connect with Milan on LinkedIn The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.  https://datastandard.io https://www.linkedin.com/company/the-data-standard https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

Derek Singh, Chief Analytics Officer at FixtHub, sits down with TDS to discuss data modeling in a fixed income space. Connect with Derek on LinkedIn The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.  https://datastandard.io https://www.linkedin.com/company/the-data-standard https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

Telematics has been widely adopted in a wide variety of industries since the turn of the millennium and has provided businesses with previously unobtainable information into both vehicle and driver performance. This has drastically simplified fleet management processes and enabled significant improvements in efficiency and productivity. Vehicles are more than transportation: they're now smart mobile devices generating large volumes of telematics data.  In this episode, guest Sajeewa Dayaratne sits down with guest host Ash Malgaonkar to discuss Data in the telematics industry.  Coretex is a complete telematics solution provider that supplies world-class fleet management and business intelligence technology, enabling transport operators to optimize the core of their business in real-time. The company's enterprise IoT platform delivers cloud-based software and in-vehicle sensor technology. Coretex believes that technology should be used to create a safer, greener, and more productive society. Connect with Sajeewa on LinkedIn The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.  https://datastandard.io https://ww w.linkedin.com/company/the-data-standard https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

Samuel Gomez, CTO at GATACA, sits down with TDS to discuss systems transitions. GATACA is a cybersecurity company that develops self-sovereign identity technology to deliver hyper-secure, passwordless, and privacy-preserving access to digital services. Connect with Samuel on LinkedIn The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.  https://datastandard.iohttps://www.linkedin.com/company/the-data-standardhttps://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

Tom Doyle, SVP, R&D at Medidata Solutions, sits down with TDS to discuss working with clinical trial software in medical data. Connect with Tom Doyle on LinkedIn The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.  https://datastandard.io https://www.linkedin.com/company/the-data-standard https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

In this episode of The Data Standard Podcast Experience, Philomena Lamoureux discusses Federated Learning and how it is impacting the technology sector in many different ways.  She was formerly the Head of AI at Blooma.ai and currently is a Data Science Manager at ResMed.  She has a strong background in federated learning systems and 10+ years of expert experience in computational modeling. During Philomena's PhD, she had a specialization in machine learning, natural language processing, and artificial intelligence solutions.  She has a passion for data science and hopes to grow the data science community with her organization titled AI Paths.  Her organization helps to bridge the gap between aspiring data scientists and industry related projects. Connect with Philomena on LinkedIn

In this episode, guest Mark Cusack sits down with TDS to discuss cloud Data Warehousing. Yellowbrick Data is a 7-year-old startup that continues to grow in the highly competitive cloud data warehouse market. Yellowbrick recently raised $75 million in its latest round of capital funding as it expands into a variety of industries, including telecom, healthcare, retail, and manufacturing. Yellowbrick describes itself as a cloud-native data warehouse.  It is available for deployment on-premises and in hybrid cloud and multi-cloud environments. Key topics from the interview include: What makes a database or data warehouse cloud-native? APIs, open-source, storage tiers,  networking. How does Yellowbrick define it? One of the key things with cloud-native data warehouses is the separation of storage and compute. It gives you scalable storage and dynamic compute resources. Not all approaches to storage/computing are the same. Yellowbrick has published a white paper that defines six different levels of storage/compute separation. There are performance and workload advantages, but also important considerations around cost.  Mark Cusack https://www.linkedin.com/in/macusack/ The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.  https://datastandard.io https://www.linkedin.com/company/the-data-standard https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

We live in an information-centric world, those who have the information have the power. And while it may seem advantageous to constantly have your finger on the pulse of data flowing about your business and the industry, it quickly becomes a challenge to make something out of all those numbers and figures. This is where data processing comes in: the capacity to research, collect, visualize and manipulate information to extract something useful from them. Control and understanding of large amounts of data is crucial to the success of a business, and data processing can help you reach the goals you've set for yourself easier. But how exactly can data processing help a business? In this episode, guest Kate McKenzie sits down with TDS to discuss the importance of data processing Kate McKenzie https://www.linkedin.com/in/kate-mckenzie-81388651/ The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.  https://datastandard.io https://www.linkedin.com/company/the-data-standard https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

The Data Standard is joined by Iwao Fusillo, Chief Data and Analytics Officer at General Motors. In this podcast, Iwao covers his journey through tech and how he began working at General Motors. He discusses empathy and mindfulness to his everyday life and workspace and how to become a mentor.  He covers advice to his own daughter and others entering the tech field. He explains how data and analytics have become demoralizing over the pandemic and how we look at this data differently since this pandemic.

Product Data Science means building data products, tools and measurement strategies that impact the consumer using a rigorous statistical methodology, expertise, and experience. In this episode, guest  Katrina Poole sits down with TDS to discuss Product Data Science.Katrina Poolehttps://www.linkedin.com/in/katrina-glaeser-poole-ab57a714/The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration. https://datastandard.iohttps://www.linkedin.com/company/the-data-standardhttps://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

Human resource departments are changing. What was an administrative function, running payroll and managing recruitment and training, is now a key player in corporate strategies and a major influence in employees' everyday work experience. How has this come about? The answer lies in people analytics. People analytics (PA) applies the power of artificial intelligence (AI) to the large data sets about people held by human resources in order to solve business problems. If a company has a problem retaining good staff, PA will tell them why and what to do about it. If sales in some shops are not as good as others, PA will identify the root of the problem in staff engagement so that the company can change managerial behavior. The range of data available to PA includes not just HR staff records, but an increasingly wide range of data types that could have movement and health data from wearable devices. Using machine learning, HR departments can identify new trends and influence people's management decisions across the company. The pitch of PA is that it replaces the vagaries of human intuition and professional experience with hard facts to create evidence-driven human resource management which brings massive efficiencies and benefits for the business. The effects of the coronavirus pandemic on employment have accelerated the practice and influence of PA. The need for safe distancing at work and expansion of home working has increased the reach of HR and the amount of data available. In this episode, guest Zach Frank sits down with TDS to discuss people Analytics and AI Zach Frankhttps://www.linkedin.com/in/zachlfrank/The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration. https://datastandard.iohttps://www.linkedin.com/company/the-data-standardhttps://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

Product Data Science means building data products, tools and measurement strategies that impact the consumer using a rigorous statistical methodology, expertise, and experience. In this episode, guest  Katrina Poole sits down with TDS to discuss Product Data Science.Katrina Poolehttps://www.linkedin.com/in/katrina-glaeser-poole-ab57a714/The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration. https://datastandard.iohttps://www.linkedin.com/company/the-data-standardhttps://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

Human resource departments are changing. What was an administrative function, running payroll and managing recruitment and training, is now a key player in corporate strategies and a major influence in employees' everyday work experience. How has this come about? The answer lies in people analytics.People analytics (PA) applies the power of artificial intelligence (AI) to the large data sets about people held by human resources in order to solve business problems. If a company has a problem retaining good staff, PA will tell them why and what to do about it. If sales in some shops are not as good as others, PA will identify the root of the problem in staff engagement so that the company can change managerial behavior.The range of data available to PA includes not just HR staff records, but an increasingly wide range of data types that could have movement and health data from wearable devices. Using machine learning, HR departments can identify new trends and influence people's management decisions across the company.The pitch of PA is that it replaces the vagaries of human intuition and professional experience with hard facts to create evidence-driven human resource management which brings massive efficiencies and benefits for the business.The effects of the coronavirus pandemic on employment have accelerated the practice and influence of PA. The need for safe distancing at work and expansion of home working has increased the reach of HR and the amount of data available.In this episode, guest Zach Frank sits down with TDS to discuss people Analytics and AIZach Frankhttps://www.linkedin.com/in/zachlfrank/The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration. https://datastandard.iohttps://www.linkedin.com/company/the-data-standardhttps://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

What do space, art, and virtual reality have in common? In two words: Sasha Samochina. In this episode, guest Sasha Samochina sits down with TDS to discuss Data visualization in the immersive space. You'll hear about Sasha's last-minute choice to go to art school and the lightbulb moment that led her to merge her love of art and science.Sasha Samochinahttps://www.linkedin.com/in/sashasamochina/The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration. https://datastandard.iohttps://www.linkedin.com/company/the-data-standardhttps://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

What do space, art, and virtual reality have in common? In two words: Sasha Samochina. In this episode, guest Sasha Samochina sits down with TDS to discuss Data visualization in the immersive space. You'll hear about Sasha's last-minute choice to go to art school and the lightbulb moment that led her to merge her love of art and science.Sasha Samochinahttps://www.linkedin.com/in/sashasamochina/The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration. https://datastandard.iohttps://www.linkedin.com/company/the-data-standardhttps://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

Stephen Drollinger, Director of Data Engineering at ICX Media, sits down with TDS to discuss his journey through tech, military life, and this company ICX Media. Stephen Drollinger https://www.linkedin.com/in/stephendrollinger/ The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.  https://datastandard.io https://www.linkedin.com/company/the-data-standard https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

Stephen Drollinger, Director of Data Engineering at ICX Media, sits down with TDS to discuss his journey through tech, military life and this company ICX Media.Stephen Drollingerhttps://www.linkedin.com/in/stephendrollinger/The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration. https://datastandard.iohttps://www.linkedin.com/company/the-data-standardhttps://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

In this episode, guest Nikhil Goyal sits down with TDS to discuss which specializations are key to building an effective data team. Prior to LeafLink, Nikhil led the data science function for Gartner's Marketing practice, gaining deep expertise in building scaled data products for large consumer brands. He has extensive experience in generating insights from e-commerce, search and transactional data leveraging experimentation, machine learning, and implementing business intelligence solutions. Nikhil has also held positions managing data science teams at and consulting F500 clients on marketing and advertising. Currently, Nikhil is responsible for continuing to evolve the data platform that powers the LeafLink marketplace. Nikhil Goyal https://www.linkedin.com/in/nikhilgoyal/ The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.  https://datastandard.io https://www.linkedin.com/company/the-data-standard https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

Management can make or break a workplace, as it is the most effective and organic way to raise productivity. Employees are usually more likely to have positive results under the right administration. There are many things that go hand-in-hand with good management. Great managers are a way of ensuring that the work that takes place somewhere will be a smooth ride to success. We can all attest to great bosses helping us thrive in our positions, but what really is it about them that makes them great? How are these people making sure that their workers stay happy while also managing to capitalize on it? Behind great management stand strategic thinkers. These are people that make strategic moves in a very humane way — they see their employees as actual people and learn to locate where their uniqueness and strengths lie. In this episode, guest Paul Carter sits down with TDS to discuss his philosophies of good management. Paul Carter https://www.linkedin.com/in/paul-w-carter/ The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.  https://datastandard.io https://www.linkedin.com/company/the-data-standard https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

Alessandro Pregnolato, VP of Data at Preply sits down with TDS to discuss business intelligence, big data, and his experience with running teams. Alessandro Pregnolato https://www.linkedin.com/in/alessandro-pregnolato-5472501/ The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.  https://datastandard.io https://www.linkedin.com/company/the-data-standard https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

From chatbots, personalized recommendations on social media, traffic predictions, and virtual personal assistants including Siri and Alexa, advances in machine learning are becoming an integral tool that helps individuals navigate the modern world. Increased adoption of such technology across the world has driven massive growth in the volume of data, requiring businesses to harness the power of machine learning to make decisions, learn about and predict customer behavior to drive strategic advantage. Combining the fields of engineering, statistics, mathematics, and computing, machine learning is one of the leading data science methodologies revolutionizing business. This course will cover a wide range of machine learning methods, both model-based and algorithmic. In this episode, guest Pierce Freeman sits down with TDS to discuss ways of bringing ML data into practice. Pierce Freeman https://www.linkedin.com/in/pierce-freeman The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.  https://datastandard.io https://www.linkedin.com/company/the-data-standard https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

In this episode, guest Nikhil Goyal sits down with TDS to discuss which specializations are key to building an effective data team. Prior to LeafLink, Nikhil led the data science function for Gartner's Marketing practice, gaining deep expertise in building scaled data products for large consumer brands. He has extensive experience in generating insights from e-commerce, search and transactional data leveraging experimentation, machine learning, and implementing business intelligence solutions. Nikhil has also held positions managing data science teams at and consulting F500 clients on marketing and advertising. Currently, Nikhil is responsible for continuing to evolve the data platform that powers the LeafLink marketplace.Nikhil Goyalhttps://www.linkedin.com/in/nikhilgoyal/The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration. https://datastandard.iohttps://www.linkedin.com/company/the-data-standardhttps://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

From chatbots, personalized recommendations on social media, traffic predictions, and virtual personal assistants including Siri and Alexa, advances in machine learning are becoming an integral tool that helps individuals navigate the modern world. Increased adoption of such technology across the world has driven massive growth in the volume of data, requiring businesses to harness the power of machine learning to make decisions, learn about and predict customer behavior to drive strategic advantage.Combining the fields of engineering, statistics, mathematics, and computing, machine learning is one of the leading data science methodologies revolutionizing business. This course will cover a wide range of machine learning methods, both model-based and algorithmic.In this episode, guest Pierce Freeman sits down with TDS to discuss ways of bringing ML data into practice.Pierce Freemanhttps://www.linkedin.com/in/pierce-freeman/The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration. https://datastandard.iohttps://www.linkedin.com/company/the-data-standardhttps://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

Management can make or break a workplace, as it is the most effective and organic way to raise productivity. Employees are usually more likely to have positive results under the right administration. There are many things that go hand-in-hand with good management.Great managers are a way of ensuring that the work that takes place somewhere will be a smooth ride to success. We can all attest to great bosses helping us thrive in our positions, but what really is it about them that makes them great? How are these people making sure that their workers stay happy while also managing to capitalize on it?Behind great management stand strategic thinkers. These are people that make strategic moves in a very humane way — they see their employees as actual people and learn to locate where their uniqueness and strengths lie.In this episode, guest Paul Carter sits down with TDS to discuss his philosophies of good management.Paul Carterhttps://www.linkedin.com/in/paul-w-carter/The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration. https://datastandard.iohttps://www.linkedin.com/company/the-data-standardhttps://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

Alessandro Pregnolato, VP of Data at Preply sits down with TDS to discuss business intelligence, big data, and his experience with running teams.Alessandro Pregnolatohttps://www.linkedin.com/in/alessandro-pregnolato-5472501/The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration. https://datastandard.iohttps://www.linkedin.com/company/the-data-standardhttps://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

When we think of computer science, namely Artificial Intelligence (AI), it's easy to forget just how revolutionary it is. Today, Artificial Intelligence can not only speak, write, listen and understand human language, it can also extract meaning from natural language to make informed decisions all thanks to Natural Language Processing. NLP is arguably one of the most exciting fields in AI and has already given rise to technologies like voice assistants, chatbots, translators, and many other tools that we use daily. Natural Language Processing is a field of AI that enables computers to analyze, understand and arrange human language. Natural language processing software continues to advance to better interpret the nuance, context, and obscurities present within human communication. NLP has already been adopted by many businesses that are driving results by drawing insights from large quantities of data while automating repetitive and monotonous tasks. NLP will only continue to benefit businesses as our reliance on, and understanding of, data shifts. With the amount of data at our disposal, it will be more and more pertinent to understand it, observe it, and in certain situations, censor it. Natural language processing will become more widespread in the years to come, as businesses reap the benefits it has to offer; from improving operations and reducing costs, to heightened customer satisfaction and more informed decision making. This episode features an interview with Kevin Wu, Chief Data Scientist at Consumer Edge. His company, Consumer Edge, enables its clients to obtain insights about the consumer from consumer transaction data. Kevin Wu https://www.linkedin.com/in/kevinwupublic/  The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration. https://datastandard.io  https://www.linkedin.com/company/the-data-standard  https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q 

Product teams are growing and with them a plethora of product suffixes: there are now product managers, owners, designers, analysts, strategists, and others all sitting on product teams. Product managers now also have more adjectives attached to their titles, whether it's based on their seniority or their field, and as the discipline evolves, so will job descriptions. But there is one conspicuous function on many product teams today that doesn't always have “product” in the title: data scientist. Data scientists facilitate data-based decision-making, experimentation, and innovation, key drivers that can put the product team ahead of the market. Being on the product team ensures they have alignment with- and a sharp focus on the product and business objectives. In this episode, guest Martin Schmitz sits down with TDS to attempt to answer the question of does every product needs a Data Scientist? Martin Schmidtz https://www.linkedin.com/in/dr-martin-schmitz/ The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration. https://datastandard.io https://www.linkedin.com/company/the-data-standard https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

When we think of computer science, namely Artificial Intelligence (AI), it's easy to forget just how revolutionary it is.Today, Artificial Intelligence can not only speak, write, listen and understand human language, it can also extract meaning from natural language to make informed decisions all thanks to Natural Language Processing. NLP is arguably one of the most exciting fields in AI and has already given rise to technologies like voice assistants, chatbots, translators, and many other tools that we use daily.Natural Language Processing is a field of AI that enables computers to analyze, understand and arrange human language. Natural language processing software continues to advance to better interpret the nuance, context, and obscurities present within human communication.NLP has already been adopted by many businesses that are driving results by drawing insights from large quantities of data while automating repetitive and monotonous tasks. NLP will only continue to benefit businesses as our reliance on, and understanding of, data shifts. With the amount of data at our disposal, it will be more and more pertinent to understand it, observe it, and in certain situations, censor it. Natural language processing will become more widespread in the years to come, as businesses reap the benefits it has to offer; from improving operations and reducing costs, to heightened customer satisfaction and more informed decision making. This episode features an interview with Kevin Wu, Chief Data Scientist at Consumer Edge. His company, Consumer Edge, enables its clients to obtain insights about the consumer from consumer transaction data.Kevin Wuhttps://www.linkedin.com/in/kevinwupublic/The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration. https://datastandard.iohttps://www.linkedin.com/company/the-data-standardhttps://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

Product teams are growing and with them a plethora of product suffixes: there are now product managers, owners, designers, analysts, strategists, and others all sitting on product teams. Product managers now also have more adjectives attached to their titles, whether it's based on their seniority or their field, and as the discipline evolves, so will job descriptions. But there is one conspicuous function on many product teams today that doesn't always have “product” in the title: data scientist. Data scientists facilitate data-based decision-making, experimentation, and innovation, key drivers that can put the product team ahead of the market. Being on the product team ensures they have alignment with- and a sharp focus on the product and business objectives.In this episode, guest Martin Schmitz sits down with TDS to attempt to answer the question of does every product needs a Data Scientist? Martin Schmidtzhttps://www.linkedin.com/in/dr-martin-schmitz/The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration. https://datastandard.iohttps://www.linkedin.com/company/the-data-standardhttps://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

The allure of the cloud, with its promises of cost benefits, greater stability, and more recently as the lynchpin of digital transformation, is well understood. But if such promises are to be realized, tech leaders need to think beyond just lifting and shifting on-prem applications into the cloud. Companies are reprioritizing their cloud initiatives, many shifting toward multi-cloud architecture and away from more traditional infrastructure. Our guest on this episode, Amit Arora, Data Scientist at Hughes Network Systems, joins TDS to dive into this “massive paradigm shift” from a static to a dynamic world, where companies are expanding beyond the investment in their traditional data center into many other areas. We discuss the advantages of this shift as well as how to organize a successful transition from a people, process and technology standpoint. We also take a deep dive into data science and data governance. Amit Arora https://www.linkedin.com/in/amit-arora-539120a/ The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration. https://datastandard.io https://www.linkedin.com/company/the-data-standard https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

The allure of the cloud, with its promises of cost benefits, greater stability, and more recently as the lynchpin of digital transformation, is well understood. But if such promises are to be realized, tech leaders need to think beyond just lifting and shifting on-prem applications into the cloud. Companies are reprioritizing their cloud initiatives, many shifting toward multi-cloud architecture and away from more traditional infrastructure. Our guest on this episode, Amit Arora, Data Scientist at Hughes Network Systems, joins TDS to dive into this “massive paradigm shift” from a static to a dynamic world, where companies are expanding beyond the investment in their traditional data center into many other areas. We discuss the advantages of this shift as well as how to organize a successful transition from a people, process and technology standpoint. We also take a deep dive into data science and data governance.Amit Arorahttps://www.linkedin.com/in/amit-arora-539120a/The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration. https://datastandard.iohttps://www.linkedin.com/company/the-data-standardhttps://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

Organizations across the globe are looking to organize, process, and unlock the value of the torrential amounts of data they generate and transform them into actionable and high-value business insights. Hence, hiring data scientists – highly skilled professional data science experts have become supercritical. Today, there is virtually no business function that cannot benefit from them. In fact, the Harvard Business Review has labeled data science as the “sexiest” career of the 21st century. However, no career is without its own challenges, and being a data scientist, despite its “sexiness” is no exception.Despite all the challenges, data scientists are the most in-demand professionals in the market. With the data world changing at a rapid pace, being a successful data scientist is not just about having the right technical skills but also about having a clear understanding of the business requirements, collaborating with different stakeholders, and convincing business executives to act upon the analysis provided.If you're a student or beginner facing challenges in the data science world and would like to learn more about overcoming them, then this podcast is for you as our guest Chester Isamay sits down with us to discuss challenges in the data science world. Chester Ismayhttps://www.linkedin.com/in/chesterismay/The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration. https://datastandard.iohttps://www.linkedin.com/company/the-data-standardhttps://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

Organizations across the globe are looking to organize, process, and unlock the value of the torrential amounts of data they generate and transform them into actionable and high-value business insights. Hence, hiring data scientists – highly skilled professional data science experts have become supercritical. Today, there is virtually no business function that cannot benefit from them. In fact, the Harvard Business Review has labeled data science as the “sexiest” career of the 21st century. However, no career is without its own challenges, and being a data scientist, despite its “sexiness” is no exception. Despite all the challenges, data scientists are the most in-demand professionals in the market. With the data world changing at a rapid pace, being a successful data scientist is not just about having the right technical skills but also about having a clear understanding of the business requirements, collaborating with different stakeholders, and convincing business executives to act upon the analysis provided. If you're a student or beginner facing challenges in the data science world and would like to learn more about overcoming them, then this podcast is for you as our guest Chester Isamay sits down with us to discuss challenges in the data science world. Chester Ismay https://www.linkedin.com/in/chesterismay/ The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration. https://datastandard.io https://www.linkedin.com/company/the-data-standard https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

The data in your data warehouse are only valuable if they are actually used. To make your data usable, you need to consider how the data are presented to end-users and how quickly users can answer their questions. In today's world, businesses are continuously evolving. With changing times a wave of transformation be it digital, be it predictive forecasting, or building the agile ways of operations that will sustain in crisis, having your data structured in the right format and accurate with respect to changing needs of your business is of prime importance. Data modeling plays a crucial role in enabling business users to make more informed, and data-driven decisions are key to success. Data Modeling is a way to structure your data to be stored in a database, and the approaches define agility of the database, query performance and value add to the information being extracted. In this episode, guest Dr. Maria Wang sits down with TDS to discuss best modeling practices and also cover some guidelines on how to build better data models that are more maintainable, more useful, and more performant. Dr. Maria Wang https://www.linkedin.com/in/zmariawang/ The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration. https://datastandard.io https://www.linkedin.com/company/the-data-standard https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

The data in your data warehouse are only valuable if they are actually used. To make your data usable, you need to consider how the data are presented to end-users and how quickly users can answer their questions. In today's world, businesses are continuously evolving. With changing times a wave of transformation be it digital, be it predictive forecasting, or building the agile ways of operations that will sustain in crisis, having your data structured in the right format and accurate with respect to changing needs of your business is of prime importance. Data modeling plays a crucial role in enabling business users to make more informed, and data-driven decisions are key to success. Data Modeling is a way to structure your data to be stored in a database, and the approaches define agility of the database, query performance and value add to the information being extracted. In this episode, guest Dr. Maria Wang sits down with TDS to discuss best modeling practices and also cover some guidelines on how to build better data models that are more maintainable, more useful, and more performant.Dr. Maria Wanghttps://www.linkedin.com/in/zmariawang/The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration. https://datastandard.iohttps://www.linkedin.com/company/the-data-standardhttps://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

In this episode, guest Elliot Winard sits down with TDS to discuss concepts such as data and leadership. Elliot Winard https://www.linkedin.com/in/elliotwinard/ The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration. https://datastandard.io https://www.linkedin.com/company/the-data-standard https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

In this episode, guest Elliot Winard sits down with TDS to discuss concepts such as data and leadership.Elliot Winardhttps://www.linkedin.com/in/elliotwinard/The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration. https://datastandard.iohttps://www.linkedin.com/company/the-data-standardhttps://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

Productionizing your Machine Learning model is an important part of any machine learning project. Deploying machine learning models from training to production requires companies to deal with the complexity of moving workloads through different pipelines and re-writing code from scratch. In this episode, guests Scott Mitchell and Charlie Moad sit down with TDS to talk about productionizing machine learning models. Scott Mitchell https://www.linkedin.com/in/smitchelus/ Charlie Moad https://www.linkedin.com/in/charles-moad/ The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration. https://datastandard.io https://www.linkedin.com/company/the-data-standard https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

In this episode, guest Shalini Agarwal sits down with TDS to discuss ways of automating repetitive tasks, how we need more data scientists to make our applications smarter; however, we can make them more efficient and accomplish more with data scientists by having automated workflows and tools. These tools can be used by non-data scientists to leverage the established workflows and remove the repetitive tasks from the mountain of tasks expected from a data scientist. Shalini Agarwal is the Director of Engineering at LinkedIn, responsible for building core experience of Sales Solutions enterprise product. Before this, she was responsible for delivering scalable Search and Data Applications while managing a global team at LinkedIn. Shalini spent nearly a decade at eBay where she shaped buyer experience and transformed her career from individual contributor to management. She is leading LinkedIn's REACH apprenticeship program since its inception, a program to hire talent coming from non-linear pathways to LinkedIn's engineering team. She has been part of Women in Tech programs for over 10 years. Her passion lies in building great software, business applications, and empowering women. Shalini Agarwal https://www.linkedin.com/in/shalini-agarwal-5b735b2/ The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration. https://datastandard.io https://www.linkedin.com/company/the-data-standard https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

In this episode, guest Rachael Weiss Riley sits down with TDS to discuss her work on the data for good space, and journey in providing support for mission-driven organizations. Rachael Weiss Riley leads Data Clinic's strategic vision and oversees the translation of data science and technology support into lasting impact for our partner organizations. Prior to Two Sigma, Rachael spent nearly a decade engaging in geospatial research to measure the influence of the built and social environment on public health outcomes. She holds a DrPH in Epidemiology from the CUNY School of Public Health, an MPH from Hunter College, a BS from Brown University, and was recently appointed to the inaugural NYC Open Data Advisory Council. Rachael Weiss Riley https://www.linkedin.com/in/rachael-weiss-riley-891a134/ The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration. https://datastandard.io https://www.linkedin.com/company/the-data-standard https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

Our guest, Stas Zhukovskiy, explains that the Solutions Engineering team is there to help customers choose appropriate products for things like security, analytics, data management, and more. The products are laid out in guides and blueprints so the client can easily understand why products are chosen and how to use them. In this episode, guest Stas Zhukovskiy sits down with TDS to discuss his career in solutions engineering and the ins and outs of the industry. Stas Zhukovskiy https://www.linkedin.com/in/stzhuk/ The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration. https://datastandard.io https://www.linkedin.com/company/the-data-standard https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q

Productionizing your Machine Learning model is an important part of any machine learning project. Deploying machine learning models from training to production requires companies to deal with the complexity of moving workloads through different pipelines and re-writing code from scratch. In this episode, guests Scott Mitchell and Charlie Moad sit down with TDS to talk about productionizing machine learning models.Scott Mitchellhttps://www.linkedin.com/in/smitchelus/Charlie Moadhttps://www.linkedin.com/in/charles-moad/The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration. https://datastandard.iohttps://www.linkedin.com/company/the-data-standardhttps://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q