10 Ways to Simplify DevOps for Data Apps with Snowflake

Most companies that build software have a strong DevOps culture and a mature tool chain in place to enable it. But for developers that need to embed a data platform into their applications to support data workloads, challenges emerge. DevOps for databases is much more complex than DevOps for code because database contain valuable data, while code is stateless. Instantly creating any number of isolated environments Reducing schema change frequency with variant data type

Ritual Improves Retention With a Modern Data Stack

A brittle ETL pipeline, a mix of different code languages and degrading warehouse performance inhibited customer retention analysis. With a modern data stack, Ritual has a 95% reduction in data pipeline issues, a 75% reduction in query times, and a threefold increase in data team velocity. By empowering the business with data, the business has seen a sustained improvement in retention.

Breaking the Silos Between Data Scientists, Eng & DevOps - MLOPs Live #6 - With Ecolab

Building scalable #AI applications that generate value in real business environments require not just advanced technologies, but also better processes for #datascience, #engineering and #devops teams to collaborate effectively. We will be deep diving into this topic on our next #MLOpsLive webinar with: Greg Hayes, Data Science Director at Ecolab and Yaron Haviv, our Co-Founder and CTO.

Are you prepared to mature to 'ready-made' data management?

When it comes to furnishing our living spaces, it seems we go through phases. When I was just setting out and leaving home, IKEA was my preferred furniture store. You make your choice, collect all the flat-pack boxes, lug them home, and after some hex key gymnastics: voilà. You’ve truly made it! Since then, I’ve drifted from the “some assembly required” phase to the “ready-made” one.