Technical Guide

Support your data workloads at scale

While boosting cost efficiency and productivity

How to increase productivity and efficiently support your data, analytics and AI workloads at scale

Download this technical guide to learn how startups and digital native businesses are solving some of their common data challenges. You’ll benefit from architecture diagrams, step-by-step solutions and quickstart guides. Learn how to support data use cases as you scale while boosting cost efficiency and productivity. You’ll also find real-life use cases from leading companies such as Grammarly, Rivian, ButcherBox, Abnormal Security, Iterable and Zipline.

Read the entire guide or dive straight into any of these specific challenges:

  • Consolidating on an open, unified data platform like the lakehouse
  • Scaling capacity and increasing performance and usability of data solutions
  • Building effective machine learning operations