The Data Stack Show
En podcast af Rudderstack
Kategorier:
392 Episoder
-
109: How Does Headless Business Intelligence Work? Featuring Artyom Keydunov and Pavel Tiunov of Cube Dev
Udgivet: 19.10.2022 -
Shop Talk: Will the Future of the Customer Data Platform Include a Shared Logic Layer?
Udgivet: 17.10.2022 -
The PRQL: What Comes to Mind When You Think of ‘Headless’?
Udgivet: 14.10.2022 -
108: You Can’t Separate Data Reliability From Workflow with Gleb Mezhanskiy of Datafold
Udgivet: 12.10.2022 -
Shop Talk: Is It Possible for Excel To Die?
Udgivet: 10.10.2022 -
The PRQL: Are Marketers the Worst Data Quality Offenders?
Udgivet: 7.10.2022 -
107: Building Modern Data Teams with dbt Labs, REI, and Robinhood
Udgivet: 5.10.2022 -
Shop Talk With Eric and Kostas: Transitioning From Consumer to Builder
Udgivet: 3.10.2022 -
The PRQL: What Can We Learn From the Patterns of Successful Data Teams?
Udgivet: 30.9.2022 -
106: Optimizing Query Workloads (and Your Snowflake Bill) with Vinoo Ganesh of Bluesky Data
Udgivet: 28.9.2022 -
Shop Talk With Eric and Kostas: Data Politicians
Udgivet: 26.9.2022 -
The PRQL: Comparing Snowflake to a Car
Udgivet: 23.9.2022 -
105: The Modern Data Stack Is Just Getting Started with Astasia Myers of Quiet Capital
Udgivet: 21.9.2022 -
The PRQL: Kostas Becomes a Prophet
Udgivet: 16.9.2022 -
104: A Decade of Change in the Data Space with Benn Stancil of Mode
Udgivet: 14.9.2022 -
The PRQL: What Does 10 Years in the Data Space Give You?
Udgivet: 9.9.2022 -
103: Everyone Is Invited to the Data Lakehouse with Kyle Weller of Onehouse.ai
Udgivet: 7.9.2022 -
The PRQL: Who Really Needs To Know How a DBMS Works?
Udgivet: 2.9.2022 -
102: Building Pinot for Real-Time, Interactive User Analytics with Kishore Gopalakrishna of StarTree
Udgivet: 31.8.2022 -
The PRQL: Data Warehouses on Steroids
Udgivet: 26.8.2022
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.