The relationship between AI assistants and data professionals is evolving rapidly, creating both opportunities and challenges. These tools can supercharge workflows by generating SQL, assisting with exploratory analysis, and connecting directly to databases—but they're far from perfect. How do you maintain the right balance between leveraging AI capabilities and preserving your fundamental skills? As data teams face mounting pressure to deliver AI-ready data and demonstrate business value, what strategies can ensure your work remains trustworthy? With issues ranging from biased algorithms to poor data quality potentially leading to serious risks, how can organizations implement responsible AI practices while still capitalizing on the positive applications of this technology? Christina Stathopoulos is an international data specialist who regularly serves as an executive advisor, consultant, educator, and public speaker. With expertise in analytics, data strategy, and data visualization, she has built a distinguished career in technology, including roles at Fortune 500 companies. Most recently, she spent over five years at Google and Waze, leading data strategy and driving cross-team projects. Her professional journey has spanned both the United States and Spain, where she has combined her passion for data, technology, and education to make data more accessible and impactful for all. Christina also plays a unique role as a “data translator,” helping to bridge the gap between business and technical teams to unlock the full value of data assets. She is the founder of Dare to Data, a consultancy created to formalize and structure her work with some of the world’s leading companies, supporting and empowering them in their data and AI journeys. Current and past clients include IBM, PepsiCo, PUMA, Shell, Whirlpool, Nitto, and Amazon Web Services.

In the episode, Richie and Christina explore the role of AI agents in data analysis, the evolving workflow with AI assistance, the importance of maintaining foundational skills, the integration of AI in data strategy, the significance of trustworthy AI, and much more.

Links Mentioned in the Show: Dare to DataJulius AIConnect with ChristinaCourse - Introduction to SQL with AIRelated Episode: The Data to AI Journey with Gerrit Kazmaier, VP & GM of Data Analytics at Google CloudRewatch RADAR AI 

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The relationship between AI and data professionals is evolving rapidly, creating both opportunities and challenges. As companies embrace AI-first strategies and experiment with AI agents, the skills needed to thrive in data roles are fundamentally changing. Is coding knowledge still essential when AI can generate code for you? How important is domain expertise when automated tools can handle technical tasks? With data engineering and analytics engineering gaining prominence, the focus is shifting toward ensuring data quality and building reliable pipelines. But where does the human fit in this increasingly automated landscape, and how can you position yourself to thrive amid these transformations? Megan Bowers is Senior Content Manager, Digital Customer Success at Alteryx, where she develops resources for the Maveryx Community. She writes technical blogs and hosts the Alter Everything podcast, spotlighting best practices from data professionals across the industry. Before joining Alteryx, Megan worked as a data analyst at Stanley Black & Decker, where she led ETL and dashboarding projects and trained teams on Alteryx and Power BI. Her transition into data began after earning a degree in Industrial Engineering and completing a data science bootcamp. Today, she focuses on creating accessible, high-impact content that helps data practitioners grow. Her favorite topics include switching career paths after college, building a professional brand on LinkedIn, writing technical blogs people actually want to read, and best practices in Alteryx, data visualization, and data storytelling. Presented by Alteryx, Alter Everything serves as a podcast dedicated to the culture of data science and analytics, showcasing insights from industry specialists. Covering a range of subjects from the use of machine learning to various analytics career trajectories, and all that lies between, Alter Everything stands as a celebration of the critical role of data literacy in a data-driven world. In the episode, Richie and Megan explore the impact of AI on job functions, the rise of AI agents in business, and the importance of domain knowledge and process analytics in data roles. They also discuss strategies for staying updated in the fast-paced world of AI and data science, and much more. Links Mentioned in the Show: Alter EverythingConnect with MeganSkill Track: Alteryx FundamentalsRelated Episode: Scaling Enterprise Analytics with Libby Duane Adams, Chief Advocacy Officer and Co-Founder of AlteryxRewatch RADAR AI  New to DataCamp? Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

We’re improving DataFramed, and we need your help! We want to hear what you have to say about the show, and how we can make it more enjoyable for you—find out more here. Imagine spending millions on data tools only to find you can’t trust the answers they provide. What if different teams define key metrics in different ways? Without a clear, unified approach, chaos reigns, and confidence erodes. What role do data governance and semantic layers play in helping you trust the AI tools you build and the insights you get from your data? Sarah Levy is a seasoned executive with extensive experience in data science, artificial intelligence, and technology leadership. Currently serving as Co-Founder and CEO of Euno since January 2023, Sarah has previously held significant positions, including VP of Data Science and Data Analytics for Real Estate at Pagaya and CTO at Sight Diagnostics, where innovative advancements in blood testing were achieved. With a strong foundation in research and development from roles at Sight Diagnostics and Natural Intelligence, as well as a robust background in cyber security gained from tenure at the IDF, Sarah has consistently driven impactful decision-making and technological advancements throughout their career. Academic credentials include a Master's degree in Condensed Matter Physics from the Weizmann Institute of Science and a Bachelor's degree in Mathematics and Physics from The Hebrew University of Jerusalem. In the episode, Richie and Sarah explore the challenges of data governance, the role of semantic layers in ensuring data trust, the emergence of analytics engineers, the integration of AI in data processes, and much more. Links Mentioned in the Show: EunoConnect with SarahCourse: Responsible AI Data ManagementRelated Episode: How Data Leaders Can Make Data Governance a Priority with Saurabh Gupta, Chief Strategy & Revenue Officer at The Modern Data CompanyRewatch sessions from RADAR: Forward Edition New to DataCamp? Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

We’re improving DataFramed, and we need your help! We want to hear what you have to say about the show, and how we can make it more enjoyable for you—find out more here. Edge computing is poised to transform industries by bringing computation and data storage closer to the source of data generation. This shift unlocks new types of value creation with data & AI and allows for a privacy-first and deeply personalized use of AI on our devices. What will the edge computing transition look like? How do you ensure applications are edge-ready, and what is the role of AI in the transition?  Derek Collison is the founder and CEO at Synadia. He is an industry veteran, entrepreneur and pioneer in large-scale distributed systems and cloud computing. Derek founded Synadia Communications and Apcera, and has held executive positions at Google, VMware, and TIBCO Software. He is also an active angel investor and a technology futurist around Artificial Intelligence, Machine Learning, IOT and Cloud Computing. Justyna Bak is VP of Marketing at Synadia. Justyna is a versatile executive bridging Marketing, Sales and Product, a spark-plug for innovation at startups and Fortune 100 and a tech expert in Data Analytics and AI, AppDev and Networking. She is an astute influencer, panelist and presenter (Google, HBR) and a respected leader in Silicon Valley and Europe. In the episode, Richie, Derek, and Justyna explore the transition from cloud to edge computing, the benefits of reduced latency, real-time decision-making in industries like manufacturing and retail, the role of AI at the edge, and the future of edge-native applications, and much more. Links Mentioned in the Show: SynadiaConnect with Derek and JustynaCourse: Understanding Cloud ComputingRelated Episode: The Database is the Operating System with Mike Stonebraker, CTO & Co-Founder At DBOSRewatch sessions from RADAR: Forward Edition New to DataCamp? Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

We’re improving DataFramed, and we need your help! We want to hear what you have to say about the show, and how we can make it more enjoyable for you—find out more here. Integrating generative AI with robust databases is becoming essential. As organizations face a plethora of database options and AI tools, making informed decisions is crucial for enhancing customer experiences and operational efficiency. How do you ensure your AI systems are powered by high-quality data? And how can these choices impact your organization's success? Gerrit Kazmaier is the VP and GM of Data Analytics at Google Cloud. Gerrit leads the development and design of Google Cloud’s data technology, which includes data warehousing and analytics. Gerrit’s mission is to build a unified data platform for all types of data processing as the foundation for the digital enterprise. Before joining Google, Gerrit served as President of the HANA & Analytics team at SAP in Germany and led the global Product, Solution & Engineering teams for Databases, Data Warehousing and Analytics. In 2015, Gerrit served as the Vice President of SAP Analytics Cloud in Vancouver, Canada. In this episode, Richie and Gerrit explore the transformative role of AI in data tools, the evolution of dashboards, the integration of AI with existing workflows, the challenges and opportunities in SQL code generation, the importance of a unified data platform, leveraging unstructured data, and much more. Links Mentioned in the Show: Google CloudConnect with GerritThinking Fast and Slow by Daniel KahnemanCourse: Introduction to GCPRelated Episode: Not Only Vector Databases: Putting Databases at the Heart of AI, with Andi Gutmans, VP and GM of Databases at GoogleRewatch sessions from RADAR: Forward Edition New to DataCamp? Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

Spatial computing is revolutionizing the way we interact with digital and physical worlds, but its adoption comes with questions about practicality and return on investment. As businesses explore this cutting-edge technology, they must consider how it can enhance productivity and streamline operations. What are the best strategies to integrate spatial computing into your current systems? How can you ensure that it not only boosts efficiency but also delivers measurable benefits to your bottom line?  Cathy Hackl is a web3 and metaverse strategist, tech futurist, speaker and author. She's worked with metaverse-related companies such as HTC VIVE, Magic Leap, and AWS, and currently consults with some of the world's leading brands, including P&G, Clinique, Ralph Lauren, Orlando Economic Partnership and more. Hackl is one of the world's first Chief Metaverse Officers and the co-founder of Journey, where she works with luxury, fashion, and beauty brands to create successful metaverse and web3 strategies and helps them build worlds in platforms like Roblox, Fortnite, Decentraland, The Sandbox, and beyond. She is widely regarded as one of the leading thinkers on the Metaverse. Irena Cronin is SVP of Product for DADOS Technology, which is making an Apple Vision Pro data analytics and visualization app. She is also the CEO of Infinite Retina, which helps companies develop and implement AI, AR, and other new technologies for their businesses. Before this, she worked as an equity research analyst and gained extensive experience in evaluating both public and private companies. In the episode, Richie, Cathy and Irina explore spatial computing, the current viability of spacial computing and it's prominence alongside the release of Apple's Vision Pro, expected effects of spatial computing on gaming and entertainment, industrial applications as well as data visualization and AI integration opportunities of spatial computing, how businesses can leverage spatial computing, future developments in the space and much more.  Links Mentioned in the Show: Cathy’s BookIrena’s BooksApple Vision ProMarvel Studios and ILM Immersive Announce 'What If...? - An Immersive Story'[Course] Artificial Intelligence (AI) StrategyRelated Episode: Why the Future of AI in Data will be Weird with Benn Stancil, CTO at Mode & Field CTO at ThoughtSpotSign up to RADAR: AI Edition New to DataCamp? Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

Databricks started out as a platform for using Spark, a big data analytics engine, but it's grown a lot since then. Databricks now allows users to leverage their data and AI projects in the same place, ensuring ease of use and consistency across operations. The Databricks platform is converging on the idea of data intelligence, but what does this mean, how will it help data teams and organizations, and where does AI fit in the picture? Ari is Databricks’ Head of Evangelism and "The Real Moneyball Guy" - the popular movie was partly based on his analytical innovations in Major League Baseball. He is a leading influencer in analytics, artificial intelligence, data science, and high-growth business innovation. Ari was previously the Global AI Evangelist at DataRobot, Nielsen’s regional VP of Analytics, Caltech Alumni of the Decade, President Emeritus of the worldwide Independent Oracle Users Group, on Intel’s AI Board of Advisors, Sports Illustrated Top Ten GM Candidate, an IBM Watson Celebrity Data Scientist, and on the Crain’s Chicago 40 Under 40. He's also written 5 books on analytics, databases, and baseball. Robin is the Field CTO at Databricks. She has consulted with hundreds of organizations on data strategy, data culture, and building diverse data teams. Robin has had an eclectic career path in technical and business functions with more than two decades in tech companies, including Microsoft and Databricks. She also has achieved multiple academic accomplishments from her juris doctorate to a masters in law to engineering leadership. From her first technical role as an entry-level consumer support engineer to her current role in the C-Suite, Robin supports creating an inclusive workplace and is the current co-chair of Women in Data Safety Committee. She was also recognized in 2023 as a Top 20 Women in Data and Tech, as well as DataIQ 100 Most Influential People in Data. In the episode, Richie, Ari, and Robin explore Databricks, the application of generative AI in improving services operations and providing data insights, data intelligence, and lakehouse technology, the wide-ranging applications of generative AI, how AI tools are changing data democratization, the challenges of data governance and management and how tools like Databricks can help, how jobs in data and AI are changing and much more.  About the AI and the Modern Data Stack DataFramed Series This week we’re releasing 4 episodes focused on how AI is changing the modern data stack and the analytics profession at large. The modern data stack is often an ambiguous and all-encompassing term, so we intentionally wanted to cover the impact of AI on the modern data stack from different angles. Here’s what you can expect: Why the Future of AI in Data will be Weird with Benn Stancil, CTO at Mode & Field CTO at ThoughtSpot — Covering how AI will change analytics workflows and tools How Databricks is Transforming Data Warehousing and AI with Ari Kaplan, Head Evangelist & Robin Sutara, Field CTO at Databricks — Covering Databricks, data intelligence and how AI tools are changing data democratizationAdding AI to the Data Warehouse with Sridhar Ramaswamy, CEO at Snowflake — Covering Snowflake and its uses, how generative AI is changing the attitudes of leaders towards data, and how to improve your data managementAccelerating AI Workflows with Nuri Cankaya, VP of AI Marketing & La Tiffaney Santucci, AI Marketing Director at Intel — Covering AI’s impact on marketing analytics, how AI is being integrated into existing products, and the democratization of AI Links Mentioned in the Show: DatabricksDelta Lakea href="https://mlflow.org/" rel="noopener...

Generative AI is here to stay—even in the 8 months since the public release of ChatGPT, there are an abundance of AI tools to help make us more productive at work and ease the stress of planning and execution of our daily lives among other things.  Already, many of us are wondering what is to come in the next 8 months, the next year, and the next decade of AI’s evolution. In the grand scheme of things, this really is just the beginning. But what should we expect in this Cambrian explosion of technology? What are the use cases being developed behind the scenes? What do we need to be mindful of when training the next generations of AI? Can we combine multiple LLMs to get better results? Bal Heroor is CEO and Principal at Mactores and has led over 150 business transformations driven by analytics and cutting-edge technology. His team at Mactores are researching and building AI, AR/VR, and Quantum computing solutions for business to gain a competitive advantage. Bal is also the Co-Founder of Aedeon—the first hyper-scale Marketplace for Data Analytics and AI talent. In the episode, Richie and Bal explore common use cases for generative AI, how it's evolving to solve enterprise problems, challenges of data governance and the importance of explainable AI, the challenges of tracking the lineage of AI and data in large organizations. Bal also touches on the shift from general-purpose generative AI models to more specialized models, fascinating use cases in the manufacturing industry, what to consider when adopting AI solutions in business, and much more. Links mentioned in the show: PulsarTrifactaAWS Clarify[Course] Introduction to ChatGPT[Course] Implementing AI Solutions in Business[Course] Generative AI Concepts

Historically in elite team sports, there has often been a dynamic between players and their inherent abilities, and the vision of the coach. In many sports, we’ve seen coaching strategies influence the future of how the game is played. As the era of professionalism swept across many elite sports in the 90s, we saw the highest-level sports teams achieve a competitive edge by looking at the data, with sports fans often noticing a difference in the ‘feel’ of the way their team plays. In Basketball specifically, we have recently seen the rise of the 3-pointer, a riskier and much more difficult shot to accurately hit, even for professional players. But what has driven the rise of the 3-pointer? Is it another trend among coaches, or does the answer lie with data-based insights and the analysts producing these insights? Seth Partnow is the Director of North American Sports at StatsBomb, where he previously served as their Director of Basketball Analytics. Prior to joining StatsBomb in 2021, Seth was the Director of Basketball Research for the Milwaukee Bucks basketball team. Seth is also an accomplished Analyst and Author, having worked as an NBA Analyst for The Athletic since 2019 and having published his own book on basketball analytics, The Midrange Theory. Seth’s knowledge and insight bridges the gap between data analytics and elite US sport.  In the episode, Seth and Richie look into the intricate dynamics of elite basketball. Seth explores the challenges of attributing individual contributions in a sport where the outcome is significantly influenced by the complex interplay between players. Drawing from his extensive experience in the field, Seth discusses the complexities of analyzing player performance, the nuances of determining why certain players get easier or harder shots, and the difficulty of attributing credit for defensive achievements to individual players. Seth provides a comprehensive overview of the various roles within sports analytics, from data engineers to analysts, and highlights the importance of finding one's niche within these roles, particularly in the context of elite basketball. Seth also shares his personal journey into basketball analytics, offering valuable insights and advice for those interested in pursuing a career in this field, stressing the importance of introspection and understanding the unique lifestyle associated with working for a sports team, while also offering industry-agnostic advice on how to approach analyzing and using data in any context.