The Data Chief

The next generation of analytics is here. In this episode of The Data Chief, ThoughtSpot CEO Ketan Karkhanis explains why AI is the new BI, and the future of analytics is autonomous. Karkhanis shares his vision for the autonomous enterprise, where AI agents act on insights and automate workflows.  He also explains why a culture of trust and experimentation is crucial for unlocking AI's full potential. Don't miss this discussion on how to fundamentally rethink how organizations interact with data to drive better business outcomes and build an autonomous enterprise.Key Moments:AI is the New BI (08:35): Ketan explains that AI represents a “foundational rewiring” of the entire technology stack, a shift he calls Cloud 2.0. He predicts the BI market is on the verge of an “upgrade super cycle,” leaving legacy players behind.AI Becomes the Only UI (20:45): Ketan shares his vision that in the future, AI will become "the only UI you will need". He explains that ThoughtSpot’s MCP host can bring together structured data, unstructured data, and world knowledge to provide better context for a user's question.Progress over Perfection (25:56): Leaders are reminded not to let “perfection be the enemy of progress.” For Ketan, a culture of trust and openness to experimentation is more important than having perfectly defined KPIs or flawless dashboards.Training Comes First (29:02): One of the biggest lessons learned was the importance of investing in people before chasing the promise of AI outcomes.  After rolling out mandatory generative AI training, new use cases began emerging organically from across the business—proof that education fuels innovation.Outcomes Over Tech (38:47): Despite mountains of legacy technology, many organizations remain starved for actionable insights. Ketan points to EasyJet as an example of getting it right: rather than focusing on systems and infrastructure, they designed their AI initiative around a tangible outcome—avoiding flight cancellations.The Rise of the Autonomous Enterprise (42:56): The next frontier is the autonomous enterprise, where AI agents don’t just surface insights but also act on them. Ketan envisions a future where humans are freed from mundane tasks to focus on higher-value work like relationships and judgment calls.Key Quotes:"AI becomes the only UI you will need." - Ketan Karkhanis"It's not about AI. It's about ROI." - Ketan Karkhanis"This is no longer just about BI. This is about agents that are driving workflows in your organizations." - Ketan KarkhanisMentions:Go Boundaryless Product SpotlightThoughtSpot Agentic MCP Server Lex Fridman PodcastTeam of Rivals: The Political Genius of Abraham LincolnThe Path Between the Seas: The Creation of the Panama CanalGuest Bio: Ketan Karkhanis is the CEO of ThoughtSpot. Prior to joining the company in September 2024, Ketan was the Executive Vice President and General Manager of Sales Cloud at Salesforce. He returned to Salesforce in March 2022 after his time as the COO of Turvo, an emerging supply-chain collaboration platform. Before that, Ketan spent nearly a decade at Salesforce, where he led product areas in Sales, Service Cloud, Lightning Platform, and finally Analytics, wherein as the Senior Vice President & GM of Einstein Analytics, he pioneered incredible innovation, customer success, and business acceleration from launch to over $300M and a 30,000 strong user community. Prior to Salesforce, Ketan was at Cisco Systems where he led various technology initiatives and initiatives spanning Customer Advocacy, Cisco Certifications & eLearning. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

Hear how data is rewriting the rules—and driving the future of innovation. Dr. Vanja breaks down his approach to enterprise AI, and the key strategies for success. He shares what it means to be a “data-forward organization” and why data must sit at the heart of how a company operates. Discover why integration speed is the new competitive edge Key Moments:Data as a Core Enterprise Asset (6:04): Dr. Vanja defines what it means to be a “data-forward organization,” emphasizing that data shouldn’t be an afterthought—it must sit at the heart of how a company operates, makes decisions, and serves customers.Relational Foundation Models for Predictive AI (16:26): Dr. Vanja explains how Kumo uses transformer architectures on raw relational data to eliminate 95% of traditional ML tasks like feature engineering—bringing pre-trained, multi-purpose prediction models into the structured data world.Integration Speed as a Competitive Edge (27:03): It's no longer just about who builds the fastest—but who integrates the fastest. Dr. Vanja shares how companies that can quickly adopt and scale best-in-class third-party tools will define the next generation of winners.The Case for Rebuilding at 10x Advantage (29:02): Dr. Vanja urges leaders to rethink old systems if a new approach offers a 10x cost or performance improvement. Sticking with outdated architectures out of fear or inertia risks falling behind during pivotal transitions.Key Quotes:“The key asset is the data that you have… You need to build the whole enterprise around this data. It’s not an afterthought — it’s at the center of the organization and how it functions.” - Dr. Vanja“Companies that integrate the fastest — not just build the fastest — will win.” - Dr. Vanja“If you really value your data, you need to stay in the cloud… If the cost is your only driver, then do what you want — but you’ll miss out on the majority of new technologies.” - Dr. VanjaMentions:Build AI Models for Relational DataThe New Cloud Era of Data Platform Hosted AppsKumo unveils world's first Relational Foundation Model (RFM) for instant predictions on enterprise dataGuest Bio: Dr. Vanja Josifovski is the Co-Founder and CEO of Kumo. Prior to Kumo, Vanja was the CTO at Airbnb & Pinterest. Here, Vanja led an organization that included horizontal groups such as Homes Engineering and Homes Data Science, as well as GM groups such as Marketplace, Relevance and Personalization, and Regulatory Frameworks. Before Airbnb, Vanja was the CTO & VP Eng at Pinterest, responsible for the overall technical vision and strategy of the company and communicating that to leadership and the teams; hiring and development of technical talent. As the head of Engineering, he managed some core engineering teams. Vanja has also served as an advisor and investor for multiple startups and was the founder for Kosei, which was acquired by Pinterest. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

Join us for expert insights on driving data-led change. Anand Iyer, Senior Vice President and Chief Data Officer at Ecolab, breaks down his approach to AI-powered innovation. He shares how to ensure AI initiatives directly impact the bottom line, why an engineering approach is key for prioritizing AI use cases, and that "garbage in, disaster out" is the new reality for data at AI scale. Discover how self-service analytics with AI is transforming data access and why AI is now a critical "business forcing function" in today's volatile world.Key Moments:The "Value First Mindset" for AI (03:13): Despite the hype around AI, initiatives must directly impact the top or bottom line in a measurable way. Sustained investment requires a clear link between the AI initiative and its financial value, moving beyond "soft benefits."Engineering Mindset for Prioritization (11:27): Anand discusses how an engineering approach is applied to prioritizing AI use cases, which helps teams focus on thoroughly understanding the problem and desired outcome before selecting a solution. "Garbage In, Disaster Out" (14:27): A new take on an old adage is introduced: "in the AI world is garbage in and disaster out". This highlights the magnified risks of bad data when leveraged at AI scale.Advocacy for Self-Service Analytics with AI (24:10): Self-service analytics is championed, describing how the integration of AI and conversational AI allows users to ask questions regarding the data. This removes the need for IT involvement in report generation and simplifies the learning curve for data structures.AI as a Business Forcing Function (33:38): In today's volatile global environment, near real-time data and AI-driven insights are no longer optional but a "business forcing function". Rapid reactions to market disruptions, policy changes, and supply chain issues are critical for a company's survival and success.Key Quotes:"If you want to have a seat at the table, you've got to be able to talk in terms of what the value is in terms of dollars." - Anand Iyer“We've deployed ThoughtSpot technology to be able to provide self-serve analytics to our teams, which allows them to have access to the data. This enables them to have conversational questions.” - Anand Iyer"The role that data, analytics, and AI play is the ability to give business leaders access to impact and what they should do in a very timely manner so that they can minimize any impact to business." - Anand IyerMentions:Before You Ask an AI Chatbot for Depression Advice, Read This'Garbage in, Garbage out': AI Fails to Debunk Disinformation, Study FindsThe Bhagavad Gita - By Bed VyasGuest Bio:Anand Iyer is the SVP, Chief Data Officer at Ecolab, where he leads the company’s global data and analytics strategy. Based in Mechanicsburg, Pennsylvania, he oversees enterprise data governance, business intelligence, engineering, and advanced analytics to accelerate Ecolab’s digital transformation. Since joining in 2018, Anand has held several senior roles, including VP of Enterprise Architecture and VP of Architecture for Commercial Digital Solutions, helping to scale IoT and data-driven platforms across the organization.With over 14 years of experience in data architecture and digital innovation, Anand has a proven track record of aligning technical solutions with business outcomes. Prior to Ecolab, he held leadership roles at GE Healthcare Digital, CSRA Inc., and CSC. He holds an engineering degree from the National Institute of Technology Rourkela and is known for building high-performing teams and cultivating a data-first culture that drives smarter, more sustainable decisions. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

Prepare for game-changing AI insights! Join Noelle Russell, CEO of the AI Leadership Institute and author of Scaling Responsible AI: From Enthusiasm to Execution. Noelle, an AI pioneer, shares her journey from the early Alexa team with Jeff Bezos, where her unique perspective shaped successful mindfulness apps. We'll explore her "I Love AI" community, which has taught over 3.4 million people. Unpack responsible, profitable AI, from the "baby tiger" analogy for AI development and organizational execution, to critical discussions around data bias and the cognitive cost of AI over-reliance.Key Moments: Journey into AI: From Jeff Bezos to Alexa (03:13): Noelle describes how she "stumbled into AI" after receiving an email from Jeff Bezos inviting her to join a new team at Amazon, later revealed to be the early Alexa team. She highlights that while she lacked inherent AI skills, her "purpose and passion" fueled her journey."I Love AI" Community & Learning (11:02): After leaving Amazon and experiencing a personal transition, Noelle created the "I Love AI" community. This free, neurodiverse space offers a safe environment for people, especially those laid off or transitioning careers, to learn AI without feeling alone, fundamentally changing their life trajectories.The "Baby Tiger" Analogy (17:21): Noelle introduces her "baby tiger" analogy for early AI model development. She explains that in the "peak of enthusiasm" (baby tiger mode), people get excited about novel AI models, but often fail to ask critical questions about scale, data needs, long-term care, or what happens if the model isn't wanted anymore.Model Selection & Explainability (32:01): Noelle stresses the importance of a clear rubric for model selection and evaluation, especially given rapid changes. She points to Stanford's HELM project (Holistic Evaluation of Language Models) as an open-source leaderboard that evaluates models on "toxicity" beyond just accuracy.Avoiding Data Bias (40:18): Noelle warns against prioritizing model selection before understanding the problem and analyzing the data landscape, as this often leads to biased outcomes and the "hammer-and-nail" problem.Cognitive Cost of AI Over-Reliance (44:43): Referencing recent industry research, Noelle warns about the potential "atrophy" of human creativity due to over-reliance on AI. Key Quotes:"Show don't tell... It's more about understanding what your review board does and how they're thinking and what their backgrounds are... And then being very thoughtful about your approach."  - Noelle Russell"When we use AI as an aid rather than as writing the whole thing or writing the title, when we use it as an aid, like, can you make this title better for me? Then our brain actually is growing. The creative synapses are firing away." Noelle Russell"Most organizations, most leaders... they're picking their model before they've even figured out what the problem will be... it's kind of like, I have a really cool hammer, everything's a nail, right?"  - Noelle RussellMentions:"I Love AI" CommunityScaling Responsible AI: From Enthusiasm to Execution - Noelle Russell"Your Brain on ChatGPT" - MIT Media LabPower to Truth: AI Narratives, Public Trust, and the New Tech Empire - StanfordMeta-learning, Social Cognition and Consciousness in Brains and MachinesHELM - A Reproductive and Transparent Framework for Evaluating Foundation ModelsGuest Bio: Noelle Russell is a multi-award-winning speaker, author, and AI Executive who specializes in transforming businesses through strategic AI adoption. She is a revenue growth + cost optimization expert, 4x Microsoft Responsible AI MVP, and named the #1 Agentic AI Leader in 2025. She has led teams at NPR, Microsoft, IBM, AWS and Amazon Alexa, and is a consistent champion for Data and AI literacy and is the founder of the "I ❤️ AI" Community teaching responsible AI for everyone.She is the founder of the AI Leadership Institute and empowers business owners to grow and scale with AI. In the last year, she has been named an awardee of the AI and Cyber Leadership Award from DCALive,  the #1 Thought Leader in Agentic AI, and a Top 10 Global Thought Leader in Generative AI by Thinkers360. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

Tune in for a masterclass in data leadership. Josh Cunningham, Group Head of Data and AI Culture at Lloyds Banking Group, unveils how this distinguished institution is boldly innovating with cutting-edge AI. Josh provides a riveting look into his unique role, which is dedicated to accelerating talent, building capabilities, and articulating data and AI's profound impact across the organization. Learn how Lloyds is rapidly expanding its data and AI graduate scheme and learn more about their ambitious quest to be the "most data literate bank". Hear how their innovative five-persona literacy framework, and engaging initiatives like the "Data and AI Summer School" and a physical "Data Escape Room," are driving their business forward on data and AI.Key Moments: The "People Side" of Data and AI (12:33): Reflecting on his career, Josh highlights his passion for the "people side" of data and AI, focusing on building teams and fostering career development. This addresses a critical industry gap where technology readiness often outpaces human capability.Scaling Data and AI Talent (17:23): Lloyds Banking Group significantly scaled its data and AI graduate scheme from approximately 10 to 100 graduates annually over three years, while demonstrating a proactive approach to balancing between AI training and tool adoption for their increasing talent pool.Data and AI Literacy Framework (22:52): Lloyds developed a data and AI literacy framework with five personas, from "data beginner" to "citizen," representing an evolving maturity lifecycle. This framework helps map and track colleagues' literacy levels over time.The Data and AI Summer School (29:06): Josh highlights this major, two-month, virtual program that offers over 200 live sessions hosted by internal and external experts. It covers diverse data and AI topics for all colleagues, from beginners to practitioners, and has attracted over 42,000 sign-ups in the previous year.The Physical Data Escape Room (32:18): Lloyds innovated with a physical data escape room that tours the UK, designed to engage colleagues (even those disengaged with data). Its puzzles, anchored to the entire data value chain, enable "learning by stealth" with phenomenal feedback. Key Quotes:"It's trying your best to meet people where they are and make it real for them. So... finding a way to anchor the learning to something that's relevant to their their day to day role, is always gonna make it land better." - Josh Cunningham"I think every organization needs to find a really well-structured balance in terms of training versus adoption." - Josh Cunningham"If I was to think about our data and AI literacy framework, we've developed a framework that consists of five personas. We've tried to break it down in terms of where people might be on their data or AI literacy journey. You can go from data beginner through to data enthusiast, through to data and AI explorer, through to storyteller, through to citizen. - Josh CunninghamMentionsLloyds Banking Group - Escape RoomLloyds Banking Group's partnership with Women in Data Lloyds Banking Group's partnership with Code First Girls The AI Daily Brief PodcastGuest Bio:Josh Cunningham is the Group Head of Data and AI Culture at Lloyds Banking Group, where he leads the Data Culture Pillar—one of five strategic pillars in the Group’s data strategy. He is focused on embedding data-driven mindsets across the organization and empowering teams to unlock the full value of data.Josh spearheads a range of initiatives, including enterprise-wide data literacy programs, innovative talent attraction efforts, and collaboration events that foster a culture of experimentation and learning. With a background in data and a deep commitment to talent development, he is passionate about transforming how large organizations cultivate data careers, scale innovation, and use insights to shape the future of banking. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

Step inside the world of data innovation as Don Vu, SVP and Chief Data and Analytics Officer at New York Life, reveals how a 180-year-old institution is embracing cutting-edge AI. Don, shares insights from his unique background, spanning Major League Baseball and retail startups, now applied to transforming the insurance industry. Hear how New York Life leverages AI to make experiences proactive and intelligent, addressing challenges like the "last mile problem" in data operationalization. Key Moments: MLB Data Insights (07:28): The conversation delves into how every baseball stadium is extensively instrumented with high-speed camera and radar technology, meticulously tracking every object on the field. This massive trove of data is then shared across all baseball clubs for in-depth analysis and the optimization of strategies.The Last Mile Problem (09:38): A critical challenge in data and AI is identified as the "last mile problem," emphasizing that the primary hurdles often lie in the operationalization, change management, adoption, and acceptance of solutions, extending far beyond the mere building of models.Data & AI in Business Strategy (13:08): The discussion highlights that data serves as the fundamental underpinning for seamless operations, while AI actively transforms experiences, making them proactive and intelligent. This deep integration of AI and data is central to New York Life's core business strategy.Data Readiness & Quality (20:08): Persistent data readiness issues are addressed, underscoring that data quality, latency, governance, and stewardship—with business owners held accountable—are absolutely crucial for both structured and unstructured data environments.AI Interoperability & Agent-Driven Future (22:43): The episode explores the importance of tracking emerging AI protocols such as MCP (Model Context Protocol) and agent-to-agent protocols. A compelling vision of the future is also shared, where AI agents act on behalf of consumers. Realizing this vision depends on interoperability across AI systems, enabling smooth, intelligent collaboration between diverse platforms.GuideMe Application & AI (32:46): New York Life's innovative "GuideMe" tool, utilized by agents during client meetings, is described as possessing incredible potential for pervasive AI integration. This integration is set to significantly supercharge both the agent and client experience, streamlining financial planning.Key Quotes:“There is this phrase that data practitioners often cite. It's like this notion of garbage in, garbage out. And data quality matters. The latency of your data is significantly important. The notion of data governance and data stewardship, with a business owner being accountable for the quality of data, is really important." - Don Vu“We think human-led protection-first holistic advice and guidance is really the key here, and we have amazing advisors, we have amazing agents throughout the country, and what we're really focused on is really enhancing them and trying to make their lives easier by having AI at their side.” - Don Vu“Data is the underpinning foundation upon which that runs seamlessly and consistently. AI is the way by which it becomes proactive and intelligent across the entire set of experiences.” - Don VuMentionsHow New York Life’s “Guide Me” is Leading the Way in Digital TransformationRockaway Beach: New York’s Best Kept SecretLeading Change: By John P. KotterDiner: South Williamsburg, Brooklyn RestaurantGuest Bio Don Vu is the Senior Vice President and Chief Data and Analytics Officer at New York Life. In this role, Don leads the company's artificial intelligence (AI) and data team, overseeing AI, data, and insights initiatives and ensuring data architecture supports New York Life's business objectives. Prior to joining New York Life, Don served as chief data officer at Northwestern Mutual, where he spearheaded organizational transformation and enterprise data and AI strategy. His impressive career also includes leadership positions at WeWork as vice president of data and analytics and 13 years at Major League Baseball (MLB) as vice president of data and analytics. Don holds a B.S. in Information Systems and Commerce from the University of Virginia and actively contributes to the field as an advisory board member for McIntire's Business Analytics program. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

Step into the future of policing where data is a mission-critical asset. Cindi Howson talks with Aimee Smith, Director of Data at the Metropolitan Police, about the Met’s bold data transformation—from digitizing records dating back to 1829 to using AI and cloud tech for smarter, faster decisions. Hear how initiatives like the V100 program and real-time analytics help improve city safety. Key Moments: Genesis of the Met’s Data Strategy (03:35) - The Met's data strategy's origin is traced to former Commissioner Cressida Dick's leadership, who envisioned leveraging data to transform policing, leading to a program building data capabilities and broadening analytics use beyond traditional intelligence and performance applications.  Mission with Data and AI (13:34): The Met's overarching mission to use data and AI for precise decision-making is articulated, acknowledging the complexity of policing's multiple goals: crime prevention, incident response, organized crime intervention, victim service, and custody safety.  Infrastructure Evolution (15:18): The transformation of the Met's data infrastructure over 5 years, from 8 separate operational systems to an integrated one with cloud technology adoption, is described, enhancing analytics and data science capabilities.  V100 Initiative (19:58): The V100 initiative, a data and analytics effort to reduce violence against women and girls by prioritizing individuals with a history of harm, is explained.  Concert Security Powered by Analytics (27:50): The use of ThoughtSpot by frontline officers is illustrated with a sergeant's innovative application for analyzing crime data around events like the Taylor Swift Eras tour to improve policing plans.  AI Agent Development (36:37): An innovative project to build an AI agent that assists frontline officers at crime scenes by providing real-time guidance is outlined, aiming to improve public protection and investigative outcomes.  Key Quotes:“So if an officer wants to start being able to do their own searches, creating their own sort of planners, thinking about doing their own trend analysis essentially, of crime data, which is great, isn't it? I mean, that's just exactly how you want ThoughtSpot to be used. Every officer has access to that.” - Aimee Smith"I like to think of it as a utility belt—you know how cops wear their utility belt? Well, hanging on there is this ThoughtSpot tool. A sergeant invented a way to use it for planning major events, concerts, to make sure our presence is right. And now that's replicable by other people who want to do the same thing." - Aimee Smith"One of the 5 principles of our business strategy for London to keep it safe is to be more precise in the use of data for decision making. So it's a high-level principle of our strategy. That makes data and analytics much harder, because there aren't enough data specialists and too many data parts to point at all those missions in one go.” - Aimee SmithMentionsMet Police’s V100 InitiativeMet Police Develops an Open Data Strategy with the Open Data InstituteMet Police’s Concert Preparation for Taylor Swift’s Eras Tour Cressida Dick Reflects on Public Trust in the Digital Age The Data Protection ActGuest Bio Aimee Smith's distinguished career in the Metropolitan Police Service (MPS) spans almost a quarter-century, truly a testament to her profound dedication to integrating robust data into the very core of police decision-making. She embarked on her journey in 2001 as an Intelligence Analyst, steadily rising through the ranks. By 2014, her leadership capabilities led her to head UK Policing’s largest Confidential Intelligence Unit. A pivotal "light-bulb moment" crystallized for her the critical importance of effective data management in driving operational outcomes, inspiring her to passionately spearhead the comprehensive MPS data transformation program. In a landmark achievement, Aimee was appointed as the first Director of Data for the MPS, where in 2019, she successfully established the inaugural Data Office within law enforcement, fundamentally reshaping how the service leverages its information. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

Embark on an insightful exploration of the hospitality sector, powered by data-driven analysis. Cindi Howson and Hyatt's data trailblazer, Ray Boyle (Vice President, Data and Analytics), are charting a course through Hyatt's data innovation. Witness how Hyatt's four-pillar data strategy is revolutionizing everything from employee empowerment to guest personalization and operational efficiency. Discover how Hyatt is democratizing data with self-service tools and pioneering an AI-powered frontier to redefine the very essence of hospitality!Key Moments: Data as an Asset (08:26): Ray emphasizes the importance of shifting the organizational mindset to view data not as a cost center, but as a critical asset. He discusses how data should be cared for, invested in, and stored like any other valuable asset, with the expectation of generating value for the business.  Hyatt's Data Strategy Pillars (13:00): Ray outlines the four key pillars that form the foundation of Hyatt's data strategy. These pillars include cultivating people and building a data-driven culture, personalizing the guest and customer experience in a high-trust environment, operating with excellence by ensuring operational efficiency and information consistency, and growing with intent by integrating new businesses and data flows.  Key Milestones in Hyatt's Data Transformation (16:42): Ray details the significant milestones in Hyatt's data transformation journey. These include clarifying the data strategy, establishing the data and AI operating model, building data governance capabilities, modernizing the data platform and infrastructure, expanding data assets, and releasing new services like personalization and forecasting.  Data Democratization and Data Fluency (23:00): Ray explains Hyatt's strong emphasis on self-service analytics to empower users across the organization. He discusses the importance of data accessibility, trustworthiness, and usability, as well as the potential of generative AI to further democratize data access and insights.  This includes building a data community to facilitate knowledge sharing and learning, as well as providing tooling and guidance to business organizations to effectively roll out analytics within their domains.  AI's Impact and Collaboration (31:35): Ray explores the transformative impact of AI on businesses and its role in fostering tighter collaboration between business and technology teams. He discusses how AI is driving the need for reimagined workflows and how it's changing the way data is used and delivered across the organization.Key Quotes:“ThoughtSpot has been a key partner of ours on that journey. We just roll the data into the cloud, and we're working to publish our assets, sales, finance, loyalty, revenue, search, and marketing into that infrastructure so that there's just a growing base of information that everybody can use in the self-service context.” - Raymond Boyle"Velocity is something you build over time. It's how I think about the operating model around data, ensuring everyone plays their role and develops the necessary skills. To me, velocity increases as you establish the operating model and you have the business, technology, and data organizations, along with governance and security, all participating effectively. - Raymond Boyle"When you think about the business outcomes and how people are beginning to consider AI's potential in that transformation, I believe AI is becoming a more significant factor every quarter." - Raymond BoyleMentionsThe Four V’s of Big Data, Including VelocityDalva, By Jim HarrisonMinnesota Timberwolves’ SuccessGuest Bio Ray Boyle (current Vice President, Data and Analytics at Hyatt) has enjoyed a distinguished career spanning several industries and roles across consulting, software, analytics, and data leadership. His notable roles include leading strategic planning, research, and analytics for Walmart’s Sam’s Club division; serving as Vice President of Walmart Global Customer Insights and Analytics; Vice President of Walmart’s Global Data and Analytics Platform; Vice President leading FICO’s global retail and CPG practice; and Executive Vice President heading IRI’s Global Shopper Analytics and Services team.Since 2019, Ray has served as Vice President, Data and Analytics at Hyatt. Aligned with Hyatt’s purpose — to care for people so they can be their best — his ambition is to elevate and scale that care through data-driven decisions and automation that benefit guests, customers, owners, and colleagues.Guest Bio Ray Boyle (current Vice President, Data and Analytics at Hyatt) has enjoyed a distinguished career spanning several industries and roles across consulting, software, analytics, and data leadership. His notable roles include leading strategic planning, research, and analytics for Walmart’s Sam’s Club division; serving as Vice President of Walmart Global Customer Insights and Analytics; Vice President of Walmart’s Global Data and Analytics Platform; Vice President leading FICO’s global retail and CPG practice; and Executive Vice President heading IRI’s Global Shopper Analytics and Services team.Since 2019, Ray has served as Vice President, Data and Analytics at Hyatt. Aligned with Hyatt’s purpose — to care for people so they can be their best — his ambition is to elevate and scale that care through data-driven decisions and automation that benefit guests, customers, owners, and colleagues. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

Prepare to see banking in a new light! Cindi Howson and Macquarie Bank's data trailblazer, Ashwin Sinha (Chief Data Officer), go deep into the AI revolution transforming financial services. Discover how one of Australia's most dynamic financial institutions, Macquarie Bank, is wielding the disruptive force of generative AI, not just for efficiency, but to combat high-stakes threats like fraud. Plus, discover the remarkable evolution of the data analyst from report-generator to AI-powered strategic powerhouse!Key Moments: Drivers of Digital Transformation (04:36): Ashwin outlines the key factors driving a digital transformation and early cloud adoption, emphasizing customer obsession, improving turnaround times, and ensuring technology reliability.  Leveraging Dual Cloud Providers (12:25): Ashwin discusses Macquarie Bank's use of AWS for infrastructure and core applications and Google Cloud (GCP) for its digital and data stack, including AI capabilities.  The Power of Gen AI in Analytics (14:16): Ashwin explores the role of generative AI in enhancing productivity for data analysts, particularly through prompt engineering and tools like ThoughtSpot.  Empowering Analysts Through Evolution (16:56): Ashwin details Macquarie Bank's successful strategy for evolving the data analyst role by proactively introducing self-service analytics, emphasizing upskilling, and enabling analysts to concentrate on higher-impact activitiesCombating Data Risk and Fraud Prevention (26:04): Ashwin discusses the increasing threat of scams and fraud and details Macquarie's two-pronged approach: educating customers and employing AI and machine learning to detect and prevent fraudulent activities.  Importance of Prompt Engineering (32:57): Ashwin stresses the significance of prompt engineering as a general-purpose technology that can drive productivity across various business functions, not just within technical roles.  Key Quotes:"There is always a big backlog in most organizations, which you cannot get done just because you do not have enough capacity. You cannot prioritize them. You cannot execute fast enough. And so, what prompt engineering and GenAI broadly does is take away the low-value tasks that you could just use AI and machine learning to do for you." - Ashwin Sinha"Prompt engineering—even though it has 'engineering' in it— I see that as a general-purpose technology. It's a bit like we've just got access to a super powerful search with a lot more analytical and reasoning capability. That's how I think of the usage of any of the foundational or large language models for, you know, the general population who are not in engineering or technical roles. Whether they're in business roles, sales and distribution, finance, marketing, or any of those functions, the use of prompt engineering just enables the next level of productivity for them. - Ashwin SinhaMentionsPrompt Engineering in the Age of AIAI Agent GovernanceThoughtSpot Spotter: Your AI AnalystScuba Diving and the History of the Liberty Shipwreck in BaliThe Importance of Child Education in IndiaGuest Bio Ashwin Sinha is the Chief Data Officer and Executive Director at Macquarie Bank, where he oversees the strategy and execution of Data and AI. Before joining Macquarie in 2019, Ashwin was a Partner at KPMG, leading the Data business. He has also held various global software engineering, start-up, and consulting roles over the past 22 years, focusing on data and digital transformations. Outside work, Ashwin is passionate about child education and macroeconomics Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

Ever wondered how data powers the magic behind your favorite theme park experiences? Join Cindi Howson and Gavin Hupp, VP of Technology, Enterprise Architecture, Data and Martech, E-commerce and Analytics at United Parks and Resorts, as they explore the complex data ecosystem of a theme park, from e-commerce and guest experience to AI's role in shaping the future of entertainment.Key Moments: Theme Park Business Model (03:12): Theme parks are described as a mix of multiple businesses, including e-commerce for ticket sales, animal experiences, entertainment venues, culinary and restaurant services, and retail operations. This combination creates a complex ecosystem, similar to city planning, within a single physical location.  Data Ecosystem Challenges (03:37): Gavin highlights the challenge of managing data within theme parks due to the variety of business areas. Each area generates unique data, leading to disparate and sometimes siloed data sets across different business applications.  AI as an Innovation Driver (11:24): AI is viewed as a key driver of innovation within the theme park industry, capable of creating new products and services, such as augmented reality experiences, and enhancing personalization at scale.  AI for Process Optimization (11:24): Beyond guest-facing innovation, AI is also seen as a tool to optimize business processes, streamline operations, reduce costs, and identify opportunities for revenue growth through personalization and increased efficiency.  Data-Driven Decision-Making (17:30): United Parks and Resorts emphasizes the importance of guest feedback, collected through surveys and other means, and uses it to inform decision-making and guide the company's overall strategy.  Agile Development Approach (28:50): Gavin explains how the company employs agile development principles, using "skateboards" as a metaphor for quickly delivering initial solutions and value while simultaneously iterating and building more comprehensive and scalable solutions ("scooters" and "factories").Key Quotes:"To become more data-driven, you have to break down silos. This requires making people aware of the silos, the challenges they create, and framing it as a data quality discussion. Getting business leaders to care about data quality isn't easy; they want end results and impact." - Gavin Hupp"There's product and service innovation, and business process innovation, where AI optimizes and streamlines operations, decreasing costs and increasing revenue through personalization." - Gavin Hupp“There's an agile concept, a principle where, at the end of the day, you need to get movement, you need to get going. And so you can use a skateboard to go from point A to point B.” - Gavin HuppMentionsGavin Hupp, Forbes ArticlePenguin Trek: Seaworld Roller CoasterConway’s Law4 Values of Agile DevelopmentScrumDiet & Eating Habits of Killer WhalesGuest Bio Gavin Hupp is currently the VP of Technology: Enterprise Architecture & Data, Martech, e-Commerce & Analytics at SeaWorld Parks & Entertainment (United Parks & Resorts). In addition, he is also a member of the Quartz CIO & CISO Advisory Board. Gavin’s expertise is helping shape the agenda to ensure it’s packed with actionable strategies and forward-thinking insights. Gavin Hupp has a strong background in technology, data, and marketing, with experience in various leadership roles in companies such as PetSmart, Denny's, and Transdev North America. Gavin has a strong educational background, with degrees from the Massachusetts Institute of Technology, Stanford University, and Western International University. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

How does SharkNinja use data to fuel its rapid growth and product innovation? Join Cindi Howson and Elpida Ormanidou, VP of Analytics and Insights at SharkNinja, as they dissect SharkNinja's data-driven culture, Elpida's journey in the data space across CPG and retail, and her insights on AI in the workplace. Key Moments: Data-Driven Culture (03:36): SharkNinja strongly emphasizes data in its culture, utilizing it to inform decision-making processes. The company is committed to using customer feedback gathered through data to drive the development and refinement of its product offerings.  CEO's Data Focus for Customer-centric Innovation (05:43): SharkNinja's CEO demonstrates a notable dedication to data by actively engaging with it. This involvement includes closely reviewing customer feedback and using data insights to guide product discussions and challenge teams to improve.  Data Ethics and Privacy (09:17): SharkNinja places a high priority on data ethics and privacy, emphasizing the importance of earning customer trust. Elpida shares how the company is committed to using customer data responsibly and has implemented strong controls to protect privacy.  AI and the Future of Work (20:31): Elpida discusses the transformative impact of AI on the future of work, characterizing it as a revolution. She emphasizes the importance of proactively addressing the changes by reskilling and upskilling the workforce to adapt to new roles and technologies.  Key Quotes:"Value gets created at the time of consumption. We create value for the business when data gets consumed, not when it gets connected, not when it gets processed, not when it gets synthesized, only when it's being used to drive decisions that create value for the company." - Elpida Ormanidou"Think of a company as a chain, where everything is interlinked to level up. Today's struggle is that while we have good AI applications, it's an art to connect them to create the next level of experience, particularly for customers. What works in a lab doesn't work the same in real life; there are so many different factors.” -Elpida Ormanidou"Where others have fear, I have hope and optimism that the more we automate and we remove mundane tasks from our day-to-day life or even our work life, the more we would be able to use our beautiful brains to reimagine and create new things that as a race will drive us forward for another 3,000 years." -Elpida OrmanidouMentions:SharkNinja Coolar: FrostVault TechnologySharkNinja HydrovacSurat: 100 Resilient Cities of the WorldMadam Curie: A Biography, By Eve CurieGuest Bio Elpida Ormanidou Elpida Ormanidou is the Vice President of Analytics & Insights at SharkNinja. She has extensive experience in data and analytics, having worked at companies like Walmart and Starbucks. At SharkNinja, she leads the data strategy and is passionate about fostering a data-driven culture. Elpida is a strong advocate for ethical data practices and responsible AI implementation. She is a recognized voice in the data and analytics community, frequently speaking at industry events and mentoring young professionals. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

How is Sephora using data to create personalized experiences that customers love? Join Cindi Howson and Manbir Paul, VP of Engineering, Data Insights & MarTech at Sephora, as they explore the role of data and AI in understanding customer needs, predicting preferences, and delivering impactful moments. Key Moments: Micro-Moments that Matter (3:30): Sephora leverages data to create impactful moments for customers, like sending a timely reminder to a traveler about their moisturizer.Modern Data & AI Stack (5:00): Manbir discusses Sephora’s best-of-breed data and AI stack, spanning cloud data platform, BI solution, cataloging, and machine learning democratization.The Power of the Semantic Layer (7:30): The semantic layer is crucial for enabling meaningful data discovery and governance. Sephora's investment in ThoughtSpot was driven by the need to enhance their semantic layer and drive intelligence in their BI space.Collaborative Data Governance (10:00): Sephora fosters a collaborative approach to data governance, with data stewards playing a key role. They identify individuals who are subject matter experts in their areas and are passionate about data to help drive governance and enrichment.Unlearning and Relearning (16:30): The challenge of keeping up with the evolving data landscape requires unlearning old practices and embracing new ones. Manbir highlights the importance of giving individuals the opportunity to look at the changing landscape from a new lens and empowering them to drive transformation.The Importance of Continuous Learning (20:30): Manbir acknowledges the challenge of balancing learning with delivering results, but stresses the importance of continuous learning in a rapidly evolving field. She notes that individuals are often willing to go above and beyond if there is a learning opportunity.Building High-Performing Teams (22:30): Manbir discusses the nuances of creating a high-performing, nimble team that can adapt to change and drive innovation. He mentions the importance of understanding the nuances that are important in transforming a team into a high-performing one.Key Quotes:"The intimate details, we always talk about getting closer to our clients. We want to experience our clients. I feel the intimate details that data gives you, getting your clients so close to you, is a very different lens to look at data from. It is a gift of feedback that the clients give to you or your consumers give to you in terms of data.”  - Manbir Paul"Democratizing these technologies is key to our tech stack. We have a multi-cloud strategy to capture the best tools. Tools, plus our BI investment, help us. ThoughtSpot was chosen for meaningful data insights, reaching clients where they interact with data and enhancing our BI intelligence." - Manbir Paul"We want to make sure that there are tools that help us enable scaled implementations in driving personalization, and that's where our Databricks platform enables us doing that."  - Manbir PaulMentionsFarmacy: Honey Halo Ultra-Hydrating Ceramide MoisturizerThe Geek Way by Andrew McAfeeGuest Bio Manbir PaulManbir Paul is VP of Engineering, Data Insights & MarTech at Sephora. Prior to this, he served as global head of ML engineering at Levi Strauss & Co.As a proactive, results-driven technology leader specializing in the retail industry, Manbir's expertise lies not just in understanding the industry's complexities, but also in harnessing the transformative power of Data and AI. With a passion deeply rooted in technological innovation, his most recent endeavors have involved leading in the realms of Data and AI to develop, scale, and implement solutions that amplify business growth Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

Join host Cindi Howson as she dives into the critical topic of diversity and inclusion in the data and AI space with Roisin McCarthy, founder of Women in Data UK, and Robin Sutara, Field CDO at Databricks. They discuss the challenges of recruiting and retaining diverse talent, the importance of male allies, and the role of AI in creating a more inclusive workforceKey Moments: The Power of Community: Building a Network for Women in Data: Roisin McCarthy shares the story behind founding Women in Data, inspired by her mother's advice to "put up or shut up." She highlights the organization's growth to 80,000 members in 120 countries and emphasizes the importance of male allies in achieving gender representation. (2:41)  From Apache Helicopters to Chief Data Officer: A Non-Traditional Journey: Robin Sutara shares her unique career path, starting with repairing Apache helicopters in the US Army and eventually becoming a CDO. She discusses the challenges she faced as a woman in tech and the importance of fixing systemic issues to achieve equity. (6:19)  The Talent Crunch: Addressing the Data Skills Gap: The conversation shifts to the shortage of qualified individuals in data and technology. Roisin McCarthy highlights the need for organizations to rethink their recruitment strategies and remove unnecessary barriers to entry. (11:31)  Closing the Pay Gap: A Shared Responsibility: Roisin and Robin discuss the persistent pay gap in the data industry and the risk of it widening further. They emphasize the importance of both individual and systemic action to achieve pay parity. (20:46)  Generative AI: A Double-Edged Sword for Recruiting: Roisin McCarthy shares a cautionary tale about the potential for bias in AI-generated job descriptions. She stresses the importance of human oversight and highlights Women in Data's work to develop technology that removes bias from job descriptions. (46:30)  The Future of Data and AI: Embracing Innovation and Inclusion: Robin Sutara expresses excitement about the potential of AI to simplify complex tasks and unlock the power of data. She emphasizes the importance of leveraging technology to innovate and create a more equitable and inclusive data workforce. (49:22)Key Quotes:"We simply do not have enough people coming into the industry. Regardless of gender, let's take that away. We do not have enough qualified individuals coming into the workplace in data and technology." - Roisin McCarthy   "We can't affect the change that this mission is so focused on reaching if we don't have everybody at the table." - Roisin McCarthy  "Hire talent that's not currently in the ecosystem, bring in people with a different perspective or a different experience or a different capability. You can teach them technology, right?" - Robin Sutara  "If I start 20% behind my male cohorts, doesn't matter how much you reward on meritocracy, I will never catch up." - Robin Sutara  "GenAI tech is there for so many things as to Robin's point to really take some of the heavy lifting out. But when we're looking to build inclusive teams, diverse, inclusive teams, I think that we just need a bit of a sense check and ensuring that we've got the human in the loop." - Roisin McCarthy  MentionsWomen in Data PodcastDatabricks BlogGuest Bios Roisin McCarthyAs a result of her own efforts, over two thousand people have moved into more satisfying roles and dozens of teams put together. Furthermore, she has managed a successful team of professional recruiters which, over the years, has placed thousands more. Today, she runs the successful recruitment firm, Datatech Analytics, and is the co-founder of the ground-breaking initiative, Women in Data UK. Over the past 19 years, McCarthy has been responsible for building some of the UK’s most cutting-edge data teams and has facilitated some of the most influential and successful careers in this sector, building relationships, influence and firm friendships along the way. McCarthy is seen as a thought-leader and an authority on careers, team development and talent acquisition in the field. Her unrivalled network of contacts, commitment to the data and analytics community and her unwavering passion for building strong, skilled teams is what makes her so unique.Robin SutaraFrom repairing Apache helicopters near the Korean DMZ to the corporate battlefield, Robin has demonstrated success in navigating the high stress, and sometimes combative, complexities of data-led transformations. She has consulted with hundreds of organisations 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 chair of Women in Data North America Committee. She was also recognized in 2023 as a Top 20 Women in Data and Tech, as well as DataIQ 100 Most Influential.  Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

Join host Cindi Howson alongside Chris Bruman, Chief Data and Analytics Officer at Dow, and Dan Futter, Chief Commercial Officer at Dow, as they explore how data-driven innovation is reshaping business and customer experiences. From the hub-and-spoke model for data management to the power of real-time insights, they discuss the role of data literacy, leadership, and AI-driven decision-making in driving success. Don’t miss this conversation on the future of AI, data strategy, and innovation.Discover the innovations that inspire Chris Bruman and Dan Futter, how data has shaped their careers, and which tech leaders they admire most.Key Moments: Revolutionizing Data: The Hub-and-Spoke Model: The Dow team highlights the shift to digital, while Cindi Howson reflects on IT’s evolution. They explain Dow’s decentralized hub-and-spoke model, balancing governance with agility for faster insights, accuracy, and career growth. (9:04)Why Data & Business Literacy Matter: Our guests stress understanding business needs, defining clear roles within the hub-and-spoke model, and supporting skill development. This approach simplifies processes, builds confidence in analytics, and drives value for Dow. (18:02)The Integrated Data Hub: A Game-Changer: Dow’s data hub slashes data science time from months to a day. Prioritizing quality over speed prevents tech debt, ensuring strong governance. Now the go-to source for innovation, it plays a crucial role in Dow’s data strategy. (28:03)Balancing Competing Demands in Industry: Our knowledgeable leaders in the industry underscore the importance of prioritizing data projects for impact. Decentralization eases bottlenecks, but demand remains high. Dow now requires senior sponsorship to ensure measurable value and optimize resources. (36:06)Key Quotes:"Too often, we wait until the project's done to figure out how to get the value and who’s going to sponsor it. We have to flip that around and secure senior sponsorship before we even start." – Chris Bruman"If I talk data mesh to my business clients, there’s going to be a blank stare, right? So we use hub and spoke—it’s more visual and makes a lot more sense. At the end of the day, it's really about decentralization." – Chris Bruman"Instead of just showing a data sheet or marketing collateral and making the customer hunt for insights, we now surface specific text, data, and even language customization—getting them straight to the front door, not just the right street." – Dan Futter"It’s not just about finding data—it’s about ensuring its integrity. Where is that data? How does it get created? Which processes generate it? How do we train people so that, from the start, it stays high-integrity?" – Dan FutterMentionsWhat is a data mesh?SpaceXIn Our Time PodcastWalking the Dog PodcastGuest Bios:Chris Bruman Chris Bruman is the Chief Data and Analytics Officer at Dow, a multinational company with operations in 31 countries that serves customers in a wide range of markets.Dan Futter Dan Futter is the Chief Commercial Officer for Dow. Through his leadership in Customer Experience and Marketing/Sales disciplines, Dow is on track to become the most customer-centric material science company in the world. He was the program lead for the design, development, and launch of the company’s groundbreaking Dow.com e-commerce platform and is passionate about the role digital technology plays in transforming customer journeys. Dan serves on the Executive Committee and is Chair of the Medals Committee of the Society of Chemical Industry America. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

Your host, Cindi Howson, and CTO of NVIDIA AI agentic software, Bartley Richardson, discuss the transformative potential of generative and agentic AI in business, focusing on customer service, HR, and workplace innovation. They explore real-world use cases, the challenges of managing diverse data sources, and the tools and technologies shaping the future of AI which lead to….Data Challenges: Cindi and Bartley discuss the complexities of managing structured, semi-structured, and unstructured data in the context of generative AI. They explore the challenges and opportunities presented by different data formats.Tools and Technologies: Bartley provides guidance for AI and tech leaders on evaluating and building AI agents, emphasizing the importance of listening to employee needs and selecting the right tools for specific use cases.Real-World Use Cases: The conversation digs into practical applications of agentic AI, with a focus on customer service and software development. Bartley highlights examples of how companies are using AI agents to improve efficiency and productivity.The Future of AI: The episode concludes with a look ahead at the future of AI, with Bartley sharing his optimism for the transformative potential of agentic AI and offering advice for data and AI leadersDiscover the creative facets that inspire Bartley and how data has been a driving force in his life since earning his PhD.Key Moments: Understand agentic AI: Bartley explains how agentic AI is one of the most exciting and transformative developments in the AI space, evolving from generative AI and LLMs (large language models) to create systems capable of taking actions on behalf of users. (2:20)  Use Case Summary - AI-Powered Agentic Workflows at NVIDIA: NVIDIA has embraced agentic AI workflows to enhance both employee efficiency and customer experience. A prime example is their implementation of Agent Morpheus, a system designed to streamline software delivery and security processes. (13:16)AI is the new HR: Bartley highlights how generative AI has been effectively applied in HR, particularly in employee handbooks and onboarding documents. HR documents, often buried in PDFs, contain a wealth of structured data, making them a rich source for AI applications. (15:26) Data ingestion within the future of data processing: Bartley hones in on the primary concern of how data is ingested and how structured queries are executed in ways that align with business needs. The technology is progressing rapidly, but refinement is still needed for impactful data usage. (37:43)Key Quotes:"Generative AI and agentic AI are really exciting because we're finally at the point where the experience of using AI meets our expectations. It's no longer just a label or something that might be statistics; it's something meaningful in our day-to-day life." -Bartley Richardson"If I had to pick the time to be alive and in this industry, it would be right now. The amount of progress just leaps every day, with new breakthroughs, announcements, or capabilities that didn't exist the day before." -Bartley Richardson"AI does not absolve you of critical thinking and this data literacy thing. If anything, it amplifies the need for this." -Bartley RichardsonMentions:How to Create a Data and AI Literate Company with Bridgestone and The Data LodgeErsilia Open Source AICEO Gemma Turon Examines Ersilia’s Impact on Biomedical ResearchThe Happiness Hypothesis: By Jonathan HaidtSetting the Table: By Danny MeyerGuest Bio:Bartley Richardson is CTO of NVIDIA AI agentic software and Director of Engineering for cybersecurity AI development and product engagement, including accelerated computing and generative AI. Previously, Bartley was a technical lead on multiple DARPA research projects. He was also the principal investigator of an Internet of Things research project which focused on applying machine and deep learning techniques to large amounts of IoT data to provide intelligence value relating to form function, and pattern-of-life. His primary research areas involve NLP and sequence-based methods applied to cyber network datasets as well as cross-domain applications of machine and deep learning solutions to tackle the growing number of cybersecurity threats. He holds a PhD in Computer Science and Engineering with a focus on AI.  Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

In this season premiere of The Data Chief podcast, your host Cindi Howson sits down with three industry visionaries to explore the trends, predictions, and must-take actions for data leaders in 2025. Get ready for a deep dive into: The generative AI revolution with Matt Turck, Partner at FirstMark CapitalThe future of data science and genAI with Steve Nouri, Founder of GenAI Works and AI for DiversityData Engineering in the Age of AI with Joe Reis, author of "Fundamentals of Data Engineering" and the upcoming "Mixed Model Arts."Plus: Hear their fun predictions for everything from sports to space travel!Key Moments:The generative AI revolution: Matt Turck, Partner at FirstMark Capital shares his insights on the evolving AI landscape, the rise of unstructured data, and why now is the time for enterprises to embrace AI. (1:40) The Future of Data Science: Steve Nouri, Founder of GenAI Works (an 8-million-strong community!) and AI for Diversity, discusses the impact of GenAI on data science roles, the ethical considerations of AI, and exciting trends like embodied AI and agentic AI. (29:36) Data Engineering in the Age of AI: Joe Reis, author of "Fundamentals of Data Engineering" and the upcoming "Mixed Model Arts," provides his expert perspective on the importance of data modeling, the need for upskilling in data teams, and the potential for a universal semantic layer. (1:00:00) Key Quotes:“I would predict that there's going to be a number of big acquisitions in our general space in 2025. This whole tension between the public markets doing very well, especially in tech, but the private markets still recovering - I think lends itself well to a wave of consolidation.”  - Matt Turck“Anything that requires democratization, I'm a big fan of. And certainly, the ability to query natural language databases and all things, making that available to everyone is a very powerful idea. You guys at ThoughtSpot know this better than anyone.” - Matt Turck“We are seeing people doing less coding, more relying on their co-pilots. It's going to evolve to become more and more robust. So we will be relying more on AI to do the coding.” - Steve Nouri“Well, that's what, you know, the tagline is, AI will do everything for you. It'll even do your laundry, the jobs that we don't like. And so you're actually saying you see a future where that actually is not too far off.” - Steve Nouri“I think that there's definitely a FOMO and a bit of a prisoner's dilemma problem with adopting AI in the organization because they're getting a lot of pressure from the top down, especially to do AI. Understanding what that means to your organization should be table stakes.” - Joe Reis“Learning never stops, investment never stops. And the best investment you can make is always improving yourself, no matter what that looks like.” Joe ReisMentions:FirstMark MAD Landscape 2024The MAD Podcast with Matt TurckAI4DiversityGenAI.WorksFundamentals of Data EngineeringJoe Reis Substack Guest Bios:Matt Turck is a Partner at FirstMark, where he focuses primarily on early-stage enterprise investing in the US and Europe. Matt is particularly active in the data, machine learning and AI space. For the last 10+ years, he has been organizing Data Driven NYC, the largest data/AI community in the US, and publishing the MAD Landscape, an annual analysis of the data/AI industry. He also hosts the weekly MAD (ML, AI, Data) Podcast. He can be followed on X/Twitter at @mattturck.Steve Nouri is the CEO and Co-founder of GenAI Works, the largest AI community. He is a renowned AI leader and Australia's ICT Professional of the Year, has revolutionized AI perspectives while championing Responsible and inclusive AI, founding a global non-profit initiative.Joe Reis, a "recovering data scientist" with 20 years in the data industry, is the co-author of the best-selling O'Reilly book, "Fundamentals of Data Engineering." He’s also the instructor for the wildly popular Data Engineering Professional Certificate on Coursera, in partnership with DeepLearning.ai and AWS.Joe’s extensive experience encompasses data engineering, data architecture, machine learning, and more. He regularly keynotes major data conferences globally, advises and invests in innovative data product companies, writes at Practical Data Modeling and his personal blog, and hosts the popular data podcasts "The Monday Morning Data Chat" and "The Joe Reis Show." In his free time, Joe is dedicated to writing new books and articles, and thinking of ways to advance the data industry. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

Key Moments: Focusing on Value with Bill Schmarzo 1:48Unlocking the Collective Genius with Walid Mehanna 4:07Building a Data-Literate Workforce with Valerie Logan 5:58Creating a Human-Centric AI Strategy with Sadie St. Lawrence 7:40Selecting the Right Tools with Katie Russell 11:23Implementing tools responsibly with Robert Garnett 16:00Why Clean Data Matters with Barr Moses 19:36Ensuring Responsible AI for the Long-Term with Dr. Gary Marcus 25:45 Key Quotes:“Data-driven is not important. Value-driven—that’s what’s important. We should focus on value.” — Bill Schmarzo, Head of Customer Data Innovation at Dell Technologies“Our role was rather to activate the organizational muscle… to try things out and tell us what has the highest opportunity and possibility.” — Walid Mehanna, Chief Data and AI Officer at Merck Group“It’s really a mindset and a muscle… we need to foster this kind of lasting change.” — Valerie Logan, CEO of the Datalodge“Teaching people to ask better questions is more about critical thinking than technology.” — Sadie St. Lawrence, Founder of the Human Machine Collaboration Institute“We wanted to make analytics accessible to everyone, combining real-time data and intuitive tools so every team member can gain insights and contribute to our mission to decarbonize.” — Katie Russell, Head of Data and Analytics at OVO Energy As we are looking at applications of AI within our environment, we are focused first on responsibility, making sure that we have a broad enough data set when we're building machine learning models, for instance. And so that's at the heart of anything that we do.” – Robert Garnett, Vice President for Government Analytics and Health Benefits Cost of Care at Elevance Health“Our world is moving towards a place where data is the product—and in that world, directionally accurate just doesn’t cut it anymore.” — Barr Moses, CEO and Co-Founder of Monte Carlo“The tech policy that we set right now is going to really affect the rest of our lives.” —  Dr. Gary Marcus, Scientist, Advisor to Governments and Corporations, and Author of Taming Silicon ValleyGuest Bios Bill Schmarzo Bill Schmarzo has extensive hands-on experience in the areas of big data, data science, designthinking, data monetization, and data economics. Bill is currently part of Dell Technology’s core data management leadership team, where he is responsible for spearheading customer co-creation engagement to identify and prioritize the key data management, data science, and data monetization requirements.Walid MehannaWalid Mehanna is Chief Data & AI Officer at Merck KGaA, Darmstadt, Germany, where he leads the company’s Data & AI organization, delivering value, governance, architecture, engineering, and operations across the company globally. With many years experience in startups, IT, and consulting major corporations, Walid encompasses a strong understanding of the intersection between business and technology. Katie RussellKatie Russell is the Data Director at OVO Energy, leading teams of Data Scientists, Data Engineers and Analysts who are transforming OVO’s data capability. As part of a technology led business, leveraging data using artificial intelligence keeps OVO truly innovative, delivering the best possible service for our customers. Rob GarnettRobert Garnett serves as Vice President for Government Analytics and Health Benefits Cost of Care at Elevance Health. In this role, he leads a data-driven organization supporting analytics and insights for Medicaid, Medicare, Commercial and enterprise customers in the areas of population health, cost of care, performance management, operational excellence, and quality improvement. Valerie LoganFounding The Data Lodge in 2019, Valerie is as committed to data literacy as it gets. With train-the-trainer bootcamps, and a peer community, she’s certifying the world’s first Data Literacy Program Leads. In 2023, The Data Lodge was acquired as the basis of a newly formed venture, Data Society Group (DSG), aimed at fostering data and AI literacy and cultural change at scale. Valerie is excited to also serve as the Chief Strategy Officer of DSG. Previously, Valerie was a Gartner Research VP in the CDO team where she pioneered Data Literacy research and was awarded Gartner’s Top Thought Leadership Award.Sadie St. LawrenceSadie St. Lawrence  is on a personal mission to create a more compassionate and connected world through technology. Having grown up on a farm in Iowa she witnessed first-hand how advancements in technology rapidly changed how we work and earn a living, which in turn affected the overall success of a community. Through her work, she noticed that while many organizations and individuals have good intentions when it comes to D&I in data careers, there was a lack of progress.Dr. Gary MarcusGary Marcus is a leading voice in artificial intelligence. He is a scientist, best-selling author, and serial entrepreneur (Founder of Robust.AI and Geometric.AI, acquired by Uber). He is well-known for his challenges to contemporary AI, anticipating many of the current limitations decades in advance, and for his research in human language development and cognitive neuroscience. An Emeritus Professor of Psychology and Neural Science at NYU, he is the author of six books. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

Description: Marni Baker Stein, Chief Content Officer at Coursera, joins host, Cindi Howson, and dives into  the impact of Generative AI on skills, diversity in tech, and the future of upskilling.Key Moments: The impact GenAI and the surge of learning demand (05:45)Why employers must prioritize AI literacy (10.32)The gender gap in AI learning and why it matters (19:40)Leveraging data to drive personalization and learner success (24:00)Predictions for the future of AI in the labor market (29.53)Key Quotes:“Generative AI is going to require us to all be a lot more emotionally intelligent because it's going to create such disruption and change. And we're all going to have to navigate the complexities of this change. We're going to have to bring our organizations through this change. That's going to take emotional intelligence as the one thing this technology isn't, is human. Understanding and human empathy is going to remain paramount.”“In terms of data and AI skills, what is extraordinary is that the demand for these skills in the last year has grown over a thousand percent. We now have seven individuals a minute enroll in GenAI content.”“Millions of people globally are deciding that it's time to upskill and reskill in these AI, regardless of whether their employer is telling them to or not. People see it happening. They're reading about it. They're hearing about it. And they're actively going out and chasing down those skills.”Mentions:  Caste: The Origins of Our Discontent by Isabel WilkersonFrom Academia to EdTech: The Path to an Equitable Education in the Digital Age Girls Who CodeMarni Baker Stein Bio: Marni Baker Stein is Coursera’s Chief Content Officer, where she oversees the company’s content and credential strategy and partner relationships. Marni has more than 25 years of experience in producing and scaling online and hybrid education programs. Prior to joining Coursera, she was Chief Academic Officer and Provost at Western Governors University, where she led its four colleges serving more than 135,000 students with programs that improved access and affordability without compromising academic quality. Before that, Marni held several leadership positions focused on access, student success, and program design at institutions such as the University of Texas, Columbia University, and the University of Pennsylvania. She earned her PhD in Educational Leadership from the University of Pennsylvania.  Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

Key MomentsFrom Engineer to Data Leader (03:05)A Mindset Shift: Business Problem First, Data Second (9:31)Learning From Missteps (11:00)The Gazelle and the Lion Analogy (14:53) The Role of AI: Do Things, Do Things Better, and Do Better Things (25:58)Built to Last versus Built to Adapt (40:01) Key Quotes"Instead of a data-first mindset, you need to have a business problem-first and data-second mindset. That has helped me transform myself as a leader quite a bit.""It’s more important to define the problem right than solving the problem. How can we understand what you’re trying to solve, and how it impacts the stakeholder?"“The head of data analytics functions need to be business problem driven, empathy driven, and not technology-first minded or AI-first minded. Our objective is to solve the business problems of the organization. Data, AI, and tech are the enablers.”"In the past, we built capabilities to last. Now, the mindset has to be to build capabilities to adapt."MentionsIs Data Quality the Biggest Threat to Humanity? With Barr Moses and Olga MaydanchikResponsible AI InstituteTwo-Pizza RuleGirl Scouts STEM ClassesFrom Cancerman to Ironman: A Police Officer's Journey of Arresting IllnessHans ZimmerDeepak Jose Biography Deepak Jose is Vice President, Head of Data Sciences & Business Intelligence at Niagara Bottling. He is a member of the Forbes Tech Council, AWS Retail and CPG Executive Advisory Forum, industry standards associations, Editorial Board for CDO Magazine, and an advisor for startups and AI analytics service companies.Before Niagara, Jose was part of global brands like Coca-Cola, Mars, ABB Group, Asurion and Mu Sigma in strategic roles driving business growth. He was named to the 2023 Consumer Good Visionaries by Consumer Goods Technology and Retail Info Systems News, the 2023 40 under 40 by CDO Magazine, the 2022 and 2023 Top 100 Innovators in Data & Analytics by Corinium Global Intelligence, the 2023 100 Most Influential AI Leaders in USA by AIM Research, the 2023 Direct 60 List by The Lead, and the 2023 DataIQ 100 lists. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

Key Moments: Disappointment With Today’s AI Systems (4:00) Congressional Inaction And The Need for AI Regulation (9:00)The Seduction of AI Propaganda (15:00)The Misguided Hypothesis of "Scale is All You Need" (23:00)Don’t Be Fooled by the Masters of AI Hype (27:00) The Global AI Race and the Need for International Cooperation (33:00)Key Quotes:“This matters. It matters as much as immigration policy or financial policy. The tech policy that we set right now is going to really affect the rest of our lives.”“We should want to have AI that can be like an oracle that can answer any question. There is value in trying to build such a technology. But, we don't actually have that technology. A lot of people are seduced into thinking that we do. But it may be decades away.”“Nobody can look you in the eye and say, ‘I understand how human intelligence works’. If they say that, they're lying to you. It's still an unexplored domain.” Mentions:  Taming Silicon Valley: How We Can Ensure AI Works for All Of Us Kluge: The Haphazard Construction of the Human MindThe Algebraic Mind: Integrating Connectionism and Cognitive Science (Learning, Development, and Conceptual Change)The EU AI ActAI Generates Covertly Racist Decisions About People Based On Their DialectDr. Gary Marcus Bio: Gary Marcus is a leading voice in artificial intelligence. He is a scientist, best-selling author, and serial entrepreneur (Founder of Robust.AI and Geometric.AI, acquired by Uber). He is well-known for his challenges to contemporary AI, anticipating many of the current limitations decades in advance, and for his research in human language development and cognitive neuroscience.An Emeritus Professor of Psychology and Neural Science at NYU, he is the author of six books, including, The Algebraic Mind, Kluge, The Birth of the Mind, the New York Times Bestseller Guitar Zero, and most recently Taming Silicon Valley: How We Can Ensure AI Works for All of Us.  He has often contributed to The New Yorker, Wired, and The New York Times. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.