Join data & analytics leaders from Starbucks, Cardinal Health, and Bol.com for a webinar panel discussion on scaling data literacy skills across your organization with a clear strategy, a pragmatic roadmap, and executive buy-in.
During our recent webinar on scaling self-service analytics, AtScale spoke with Kwan Lee, EVP of Engineering at EverQuote about its multifaceted self-service approach to data analytics for business users and machine learning.
The benefit of implementing analytics policies at the semantic layer – for both access control and usage policies – is that users can be guided and coached how to interact with analytics in real-time. This empowers individuals to operate independently and with confidence that they are working with data in the right way.
AtScale’s semantic layer platform can be a key enabler by addressing some of these fundamental challenges head on. Here are 10 important ways an AtScale semantic layer can help.
Predictions based on time-series analysis are one of the most common products delivered by data science teams. This post focuses on how AtScale + Snowflake create a powerful combination in this common use case.