Listen to this episode from Data Engineering Podcast on Spotify. Summary Data has been one of the most substantial drivers of business and economic value for the past few decades. Bob Muglia has had a front-row seat to many of the major shifts driven by technology over his career. In his recent book "Datapreneurs" he reflects on the people and businesses that he has known and worked with and how they relied on data to deliver valuable services and drive meaningful change. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Introducing RudderStack Profiles. RudderStack Profiles takes the SaaS guesswork and SQL grunt work out of building complete customer profiles so you can quickly ship actionable, enriched data to every downstream team. You specify the customer traits, then Profiles runs the joins and computations for you to create complete customer profiles. Get all of the details and try the new product today at dataengineeringpodcast.com/rudderstack (https://www.dataengineeringpodcast.com/rudderstack) Your host is Tobias Macey and today I'm interviewing Bob Muglia about his recent book about the idea of "Datapreneurs" and the role of data in the modern economy Interview Introduction How did you get involved in the area of data management? Can you describe what your concept of a "Datapreneur" is? How is this distinct from the common idea of an entreprenur? What do you see as the key inflection points in data technologies and their impacts on business capabilities over the past ~30 years? In your role as the CEO of Snowflake you had a first-row seat for the rise of the "modern data stack". What do you see as the main positive and negative impacts of that paradigm? What are the key issues that are yet to be solved in that ecosmnjjystem? For technologists who are thinking about launching new ventures, what are the key pieces of advice that you would like to share? What do you see as the short/medium/long-term impact of AI on the technical, business, and societal arenas? What are the most interesting, innovative, or unexpected ways that you have seen business leaders use data to drive their vision? What are the most interesting, unexpected, or challenging lessons that you have learned while working on the Datapreneurs book? What are your key predictions for the future impact of data on the technical/economic/business landscapes? Contact Info LinkedIn (https://www.linkedin.com/in/bob-muglia-714ba592/) Parting Question From your perspective, what is the biggest gap in the tooling or technology for data management today? Closing Announcements Thank you for listening! Don't forget to check out our other shows. Podcast.__init__ (https://www.pythonpodcast.com) covers the Python language, its community, and the innovative ways it is being used. The Machine Learning Podcast (https://www.themachinelearningpodcast.com) helps you go from idea to production with machine learning. Visit the site (https://www.dataengineeringpodcast.com) to subscribe to the show, sign up for the mailing list, and read the show notes. If you've learned something or tried out a project from the show then tell us about it! Email hosts@dataengineeringpodcast.com (mailto:hosts@dataengineeringpodcast.com)) with your story. To help other people find the show please leave a review on Apple Podcasts (https://podcasts.apple.com/us/podcast/data-engineering-podcast/id1193040557) and tell your friends and co-workers Links Datapreneurs Book (https://www.thedatapreneurs.com/) SQL Server (https://en.wikipedia.org/wiki/Microsoft_SQL_Server) Snowflake (https://www.snowflake.com/en/) Z80 Processor (https://en.wikipedia.org/wiki/Zilog_Z80) Navigational Database (https://en.wikipedia.org/wiki/Navigational_database) System R (https://en.wikipedia.org/wiki/IBM_System_R) Redshift (https://aws.amazon.com/redshift/) Microsoft Fabric (https://www.microsoft.com/en-us/microsoft-fabric) Databricks (https://www.databricks.com/) Looker (https://cloud.google.com/looker/) Fivetran (https://www.fivetran.com/) Podcast Episode (https://www.dataengineeringpodcast.com/fivetran-data-replication-episode-93/) Databricks Unity Catalog (https://www.databricks.com/product/unity-catalog) RelationalAI (https://relational.ai/) 6th Normal Form (https://en.wikipedia.org/wiki/Sixth_normal_form) Pinecone Vector DB (https://www.pinecone.io/) Podcast Episode (https://www.dataengineeringpodcast.com/pinecone-vector-database-similarity-search-episode-189/) Perplexity AI (https://www.perplexity.ai/) The intro and outro music is from The Hug (http://freemusicarchive.org/music/The_Freak_Fandango_Orchestra/Love_death_and_a_drunken_monkey/04_-_The_Hug) by The Freak Fandango Orchestra (http://freemusicarchive.org/music/The_Freak_Fandango_Orchestra/) / CC BY-SA (http://creativecommons.org/licenses/by-sa/3.0/)
