AI is only effective when the data it uses is consistent, well-managed, and easy to access. However, many teams still face scattered pipelines, inconsistent access controls, and rising cloud costs.
As a result, controlling expenses has become a significant cloud challenge for most companies, and wasted spending often appears first in data and AI projects.
This eBook explains how to build a Lakehouse foundation on the Databricks Data Intelligence Platform. With this approach, your data and AI projects can work together as a single process instead of separate tasks.
Inside, you’ll learn how to:
- Achieve results faster, in weeks instead of months, by using proven methods for managed pipelines, MLOps, and drift monitoring.
- Leverage tools such as Delta Lake, Unity Catalog, Workflows/DLT, Databricks SQL, and the Data Intelligence Engine to create consistent ways to store, secure, share, and interpret your data.
- Set up the right balance of advisory, engineering, AI/ML, and governance work, while making sure security and audits are handled from the start.
You’ll also get real proof points- from $3M annual savings.
Download the eBook to find a practical starting point so you can move one use case into production with a clear plan for growth and scale.