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 activities
• Combating 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 Sinha

Mentions

• Prompt Engineering in the Age of AI
• AI Agent Governance
• ThoughtSpot Spotter: Your AI Analyst
• Scuba Diving and the History of the Liberty Shipwreck in Bali
• The Importance of Child Education in India

Guest 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.

Prepare to see banking in a new light! Cindi Howson and Macquarie Bank's data trailblazer, Ashwin Sinha (Chief Data Officer and Executive Director), 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'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 activities
• Combating 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:

• "Users can then apply their own natural language query, which, with ThoughtSpot, Spotter, and Analyst Studio, allows them a good level of self-service with respect to analytics. I know ThoughtSpot was again early on this journey with respect to enabling a lot of these capabilities. I was curious about this concept all the way back in 2013, but finally, when I saw ThoughtSpot, I was like, 'Yeah, this could really work at an enterprise grade.'" - Ashwin Sinha
• "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 Sinha

Mentions

• Prompt Engineering in the Age of AI
• AI Agent Governance
• ThoughtSpot Spotter: Your AI Analyst
• Scuba Diving and the History of the Liberty Shipwreck in Bali
• The Importance of Child Education in India

Guest 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. 

Consulting at KPMG, where he focused on information strategy, digital platforms, large-scale data engineering, artificial intelligence, and emerging technology. Before joining KPMG Australia, he worked for Certus Solutions as a Practice Lead of Data Analytics, where he created and managed growth and profitability across Australia and New Zealand. Previously, he served as a Principal Engineer at Zero Degree Consulting. He also served as a Senior Data Engineer at Lloyds Banking Group and Lead Engineer of Datamatics at Aviva. Sinha holds a Bachelor's degree in Mechanical Engineering from Nagpur University.

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 Hupp

Mentions

• Gavin Hupp, Forbes Article
• Penguin Trek: Seaworld Roller Coaster
• Conway’s Law
• 4 Values of Agile Development
• Scrum
• Diet & Eating Habits of Killer Whales

Guest 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 Ormanidou

Mentions:

• SharkNinja Coolar: FrostVault Technology
• SharkNinja Hydrovac
• Surat: 100 Resilient Cities of the World
• Madam Curie: A Biography, By Eve Curie

Guest 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 Paul

Mentions

• Farmacy: Honey Halo Ultra-Hydrating Ceramide Moisturizer
• The Geek Way by Andrew McAfee

Guest Bio 

Manbir Paul

Manbir 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 workforce

Key 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  

Mentions

• Women in Data Podcast
• Databricks Blog

Guest Bios 

Roisin McCarthy

As 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 Sutara

From 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 Futter

Mentions

• What is a data mesh?
• SpaceX
• In Our Time Podcast
• Walking the Dog Podcast

Guest 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 leaders

Discover 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 Richardson

Mentions:

• How to Create a Data and AI Literate Company with Bridgestone and The Data Lodge
• Ersilia Open Source AI
• CEO Gemma Turon Examines Ersilia’s Impact on Biomedical Research
• The Happiness Hypothesis: By Jonathan Haidt
• Setting the Table: By Danny Meyer

Guest 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 Capital
• The future of data science and genAI with Steve Nouri, Founder of GenAI Works and AI for Diversity
• Data 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 Reis

Mentions:

• FirstMark MAD Landscape 2024
• The MAD Podcast with Matt Turck
• AI4Diversity
• GenAI.Works
• Fundamentals of Data Engineering
• Joe 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 1:48
• Unlocking the Collective Genius with Walid Mehanna 4:07
• Building a Data-Literate Workforce with Valerie Logan 5:58
• Creating a Human-Centric AI Strategy with Sadie St. Lawrence 7:40
• Selecting the Right Tools with Katie Russell 11:23
• Implementing tools responsibly with Robert Garnett 16:00
• Why Clean Data Matters with Barr Moses 19:36
• Ensuring 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 Valley

Guest Bios 

Bill Schmarzo 

Bill Schmarzo has extensive hands-on experience in the areas of big data, data science, design

thinking, 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 Mehanna

Walid 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 Russell

Katie 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 Garnett

Robert 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 Logan

Founding 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. Lawrence

Sadie 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 Marcus

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.

Hear more from Cindi Howson here. Sponsored by ThoughtSpot.