The Data Stack Show
Podcast autorstwa Rudderstack
440 Odcinki
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95: How the Metrics Layer Bridges the Gap Between Data & Business with Nick Handel of Transform
Opublikowany: 13.07.2022 -
The PRQL: Data Marts Aren’t Just for the Enterprise
Opublikowany: 8.07.2022 -
94: Notebooks Aren’t Just for Data Scientists With Barry McCardel of Hex Technologies
Opublikowany: 6.07.2022 -
The PRQL: Have You Ever Been a Part of a Company That Has Done Analytics Really Well?
Opublikowany: 1.07.2022 -
93: There Is No Data Observability Without Lineage with Kevin Hu of Metaplane
Opublikowany: 29.06.2022 -
The PRQL: What Are the Similarities Between VCs and Tilapia?
Opublikowany: 24.06.2022 -
92: Building a Decentralized Storage System for Media File Collaboration with Tejas Chopra
Opublikowany: 22.06.2022 -
The PRQL: What is Netflix Cloud?
Opublikowany: 17.06.2022 -
91: The Future of Streaming Data with Stripe, Deephaven, Materialize, and Benthos
Opublikowany: 15.06.2022 -
The PRQL: Can Streaming Simplify Your Data Flows?
Opublikowany: 10.06.2022 -
90: The Modern Data Stack Has a Join Problem with Ahmed Elsamadisi of Narrator AI
Opublikowany: 8.06.2022 -
The PRQL: Can One Table Rule Them All?
Opublikowany: 3.06.2022 -
89: Solving Microservice Orchestration Issues at Netflix with Viren Baraiya of Orkes
Opublikowany: 1.06.2022 -
The PRQL: What are the Different Flavors of Orchestration?
Opublikowany: 27.05.2022 -
88: What Is Data Observability? With Tristan Spaulding of Acceldata
Opublikowany: 25.05.2022 -
The PRQL: Does Data Exist if We Do Not Observe It?
Opublikowany: 20.05.2022 -
87: Why Is Now the Golden Age of Data Analytics? With Cindi Howson of ThoughtSpot
Opublikowany: 18.05.2022 -
The PRQL: Can You Trust AI Enabled Analytics?
Opublikowany: 13.05.2022 -
86: Solving the Data Quality Problem with Bigeye, Great Expectations, Metaplane, and Lightup.ai
Opublikowany: 11.05.2022 -
85: You Can Stop Doing Data Fire Drills with Barr Moses of Monte Carlo
Opublikowany: 4.05.2022
Each week we’ll talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering data and data products, and driving better outcomes across their businesses with data.
