DataFramed DataCamp

In almost every industry, the rate of innovation is increasing, and this is great for consumers around the globe. However, with constant innovation and continual disruption of the status quo, where to innovate next becomes much harder to identify. If your industry hasn’t been disrupted yet, it’s next on the list. So, in order to deal with uncertainty, a new culture is needed, and there’s a clear group of companies that constantly deal with uncertainty and innovation—VC’s. 
Ilya A. Strebulaev is the David S. Lobel Professor of Private Equity and Professor of Finance at the Stanford Graduate School of Business, and a Research Associate at the National Bureau of Economic Research. He is an expert in corporate finance, venture capital, innovation financing, and financial decision-making. He is the founder and director of the Stanford GSB Venture Capital Initiative.
In the episode, Richie and Ilya explore the venture mindset, the importance of embracing unknowns, how VC’s deal with unpredictability, how our education affects our decision-making ability, practical examples from Ilya’s teaching experiences at Stanford, adapting to market changes and continual innovation, venture mindset principles and much more. 
Links Mentioned in the Show:
Ilya’s WebsiteSequoia CapitalStanford University Related Episode: Making Better Decisions using Data & AI with Cassie Kozyrkov, Google's First Chief Decision ScientistSign up to RADAR: AI Edition
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Speedily adopting new technologies can give your business a competitive advantage, but with so much happening in the world of generative AI, it's difficult to know what to adopt. In this episode, Richie chats to two venture capitalists to get their view on the global AI landscape, where we are in the AI hype cycle, and how to adopt AI tech. Beyond this, we explore Rocketship.vc's use of data and algorithms to make investment decisions in early-stage startups. If our previous episode’s deep dive into 2024’s data & AI trends with VC Tom Tunguz got you excited about how investors are looking at the market at the moment, then this episode is sure to do the same. This time, we have twice the insight, thanks to our two guests.
Madhu Shalini Iyer is a Managing Partner at Rocketship.vc, a Silicon Valley based fund investing globally. She was the Chief Data Officer of Gojek and helped grow the business into a $10 billion unicorn. In addition to being a board member, she started the Singapore office and played an active role in the strategy, new business development, and ‘data as a competitive advantage’. Prior to Gojek, Madhu was part of the founding team of Intuit’s Quickbooks Lending Platform. As the data science leader at Intuit, Madhu helped grow the platform to $300 million and holds 2 patents in the areas of user data augmented algorithms for financial inclusion. Madhu was also the Chief Data Officer for Ethoslending. There she built the underwriting platform and was responsible for all b2c revenue, resulting in $65 million gross market value per month. Madhu was further responsible for building and running the marketing team. Prior, Madhu was a partner at a $150m private equity fund, Stem Financial, in Hong Kong. She started her career as a senior data scientist with a leading think tank in Menlo Park, CA.
Sailesh Ramakrishnan is also a Managing Partner at Rocketship.vc. Prior to Rocketship.vc, Sailesh was CTO and co-founder of LocBox (acquired by Square), a startup focussed on marketing for local businesses. Sailesh worked with Anand and Venky at their previous startup Kosmix, and continued on to Walmart as a Director of Engineering at @WalmartLabs. Before jumping into the startup world, Sailesh worked as a Computer Scientist at NASA Ames Research Center. Sailesh earned his Bachelors degree in Civil Engineering from IIT Madras, his Masters degree in Construction Management from Virginia Tech and another Master degree in Intelligent Systems from University of Pittsburgh. He was a Ph.D. candidate in Artificial Intelligence at the University of Michigan.
In the episode, Richie, Madhu and Sailesh explore the generative AI revolution, categorizing generative AI tools, the impact of genAI across industries, investment philosophy and data-driven decision-making, the challenges and opportunities when investing in AI, future trends and predictions, regulatory and ethical considerations of AI, and much more. 
Links Mentioned in the Show:
Rocketship.vc[Course] Implementing AI Solutions in BusinessRelated Episode: Inside Algorithmic Trading with Anthony Markham, Vice President, Quantitative Developer at Deutsche BankSign up to RADAR: AI Edition
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Rapid change seems to be the new norm within the data and AI space, and due to the ecosystem constantly changing, it can be tricky to keep up. Fortunately, any self-respecting venture capitalist looking into data and AI will stay on top of what’s changing and where the next big breakthroughs are likely to come from. We all want to know which important trends are emerging and how we can take advantage of them, so why not learn from a leading VC. 
Tomasz Tunguz is a General Partner at Theory Ventures, a $235m early-stage venture capital firm. He blogs sat tomtunguz.com & co-authored Winning with Data. He has worked or works with Looker, Kustomer, Monte Carlo, Dremio, Omni, Hex, Spot, Arbitrum, Sui & many others.
He was previously the product manager for Google's social media monetization team, including the Google-MySpace partnership, and managed the launches of AdSense into six new markets in Europe and Asia. Before Google, Tunguz developed systems for the Department of Homeland Security at Appian Corporation. 
In the episode, Richie and Tom explore trends in generative AI, the impact of AI on professional fields, cloud+local hybrid workflows, data security, and changes in data warehousing through the use of integrated AI tools, the future of business intelligence and data analytics, the challenges and opportunities surrounding AI in the corporate sector. You'll also get to discover Tom's picks for the hottest new data startups.
Links Mentioned in the Show:
Tom’s BlogTheory VenturesArticle: What Air Canada Lost In ‘Remarkable’ Lying AI Chatbot Case[Course] Implementing AI Solutions in BusinessRelated Episode: Making Better Decisions using Data & AI with Cassie Kozyrkov, Google's First Chief Decision ScientistSign up to RADAR: AI Edition
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With seemingly every organization wanting to enhance their AI capabilities, questions arise about who should be in charge of these initiatives. At the moment, it’s likely a CTO, CIO, or CDO, or a mixture of the three. The gold standard is to have someone in the C-suite whose sole focus is their AI projects: the Chief AI Officer. This role is so new that it's not yet widely understood. In this episode, we explore what the CAIO job entails.
Philipp Herzig is the Chief AI Officer at SAP. He’s held a variety of roles within SAP, most recently SVP Head of Cross Product Engineering & Experience, however his experience covers intelligent enterprise & cross-architecture, head of engineering for cloud-native apps, a software development manager, and product owner. 
In the full episode, Richie and Philipp explore what his day-to-day responsibilities are as a CAIO, the holistic approach to cross-team collaboration, non-technical interdepartmental work, AI strategy and implementation, challenges and success metrics, how to approach high-value AI use cases, insights into current AI developments and the importance of continuous learning, the exciting future of AI and much more. 

Links Mentioned in the Show:
SAP’s AI CoPilot JouleSAP[Course] Implementing AI Solutions in BusinessRelated Episode: How Walmart Leverages Data & AI with Swati Kirti, Sr Director of Data Science at WalmartRewatch sessions from RADAR: The Analytics Edition

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Countless companies invest in their data quality, but often, the effort from their investment is not fully realized in the output. It seems like, despite the critical importance of data quality, data governance might be suffering from a branding issue. Data governance is sometimes looked at as the data police, but this is far from the truth. So, how can we change perspectives and introduce fun into data governance?
Tiankai Feng is a Principal Data Consultant and Data Strategy & Data Governance Lead at Thoughtworks, He also works part-time as the Head of Marketing at DAMA Germany. Tiankai has had many data hats in his career—marketing data analyst, data product owner, analytics capability lead, and data governance leader for the last few years. He has found a passion for the human side of data—how to collaborate, coordinate, and communicate around data. TIankai often uses his music and humor to make data more approachable and fun.
In the episode, Adel and Tiankai explore the importance of data governance in data-driven organizations, the challenges of data governance, how to define success criteria and measure the ROI of governance initiatives, non-invasive and creative approaches to data governance, the implications of generative AI on data governance, regulatory considerations, organizational culture and much more. 
Links Mentioned in the Show:
Tiankai’s YouTube ChannelData Governance Fundamentals Cheat Sheet[Webinar] Unpacking the Fun in Data Governance: The Key to Scaling Data Quality[Course] Data Governance ConceptsRewatch sessions from RADAR: The Analytics Edition
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Databases are ubiquitous, and you don’t need to be a data practitioner to know that all data everywhere is stored in a database—or is it? While the majority of data around the world lives in a database, the data that helps run the heart of our operating systems—the core functions of our computers— is not stored in the same place as everywhere else. This is due to database storage sitting ‘above’ the operating system, requiring the OS to run before the databases can be used. But what if the OS was built ‘on top’ of a database? What difference could this fundamental change make to how we use computers?
Mike Stonebraker is a distinguished computer scientist known for his foundational work in database systems, he is also currently CTO & Co-Founder At DBOS. His extensive career includes significant contributions through academic prototypes and commercial startups, leading to the creation of several pivotal relational database companies such as Ingres Corporation, Illustra, Paradigm4, StreamBase Systems, Tamr, Vertica, and VoltDB. Stonebraker's role as chief technical officer at Informix and his influential research earned him the prestigious 2014 Turing Award.
Stonebraker's professional journey spans two major phases: initially at the University of California, Berkeley, focusing on relational database management systems like Ingres and Postgres, and later, from 2001 at the Massachusetts Institute of Technology (MIT), where he pioneered advanced data management techniques including C-Store, H-Store, SciDB, and DBOS. He remains a professor emeritus at UC Berkeley and continues to influence as an adjunct professor at MIT’s Computer Science and Artificial Intelligence Laboratory. Stonebraker is also recognized for his editorial work on the book "Readings in Database Systems."
In the episode, Richie and Mike explore the the success of PostgreSQL, the evolution of SQL databases, the shift towards cloud computing and what that means in practice when migrating to the cloud, the impact of disaggregated storage, software and serverless trends, the role of databases in facilitating new data and AI trends, DBOS and it’s advantages for security, and much more. 
Links Mentioned in the Show:
DBOSPaper: What Goes Around Comes Around[Course] Understanding Cloud ComputingRelated Episode: Scaling Enterprise Analytics with Libby Duane Adams, Chief Advocacy Officer and Co-Founder of AlteryxRewatch sessions from RADAR: The Analytics Edition
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