Databricks Procurement Strategy. A buyer side white paper.

Databricks is the principal Lakehouse framework provider, anchoring the broader cloud data and ML framework against the unified analytics framework.

Databricks segments the broader Databricks framework across the following modules:

• Databricks Data Engineering framework
• Databricks SQL framework
• Databricks Machine Learning framework
• Databricks Delta Live Tables framework
• Databricks Unity Catalog framework
• Databricks Mosaic AI framework
• Bespoke Databricks framework at the upper customer scale

This paper sets out the buyer side framework for Databricks procurement strategy, the DBU framework (Databricks Unit consumption), the multi cloud Databricks framework, the BigQuery vs Snowflake vs Databricks competitive framework, and the buyer side moves at the broader Databricks renewal cycle. Read the related Vendor Shield, the Snowflake negotiation, and the BigQuery cost governance negotiation.

What you will learn

• How Databricks Lakehouse anchors the broader cloud data and ML framework
• How the Databricks Data Engineering, SQL, Machine Learning, Delta Live Tables, Unity Catalog, and Mosaic AI frameworks segment the broader Databricks framework
• How the DBU (Databricks Unit) framework anchors the broader Databricks compute framework
• How the multi cloud Databricks framework runs across AWS, Azure, and Google Cloud
• How BigQuery vs Snowflake vs Databricks competitive framework typically delivers material commercial leverage
• How the Databricks commit framework anchors the broader Databricks framework
• The eleven move buyer side framework for Databricks procurement
• How to anchor the broader Databricks framework against the customer actual Databricks deployment framework

Table of contents

Who this is for

Chief Information Officers, Chief Data Officers, Chief AI Officers, Vice Presidents of IT Procurement, Cloud FinOps leaders, Data Platform leaders, ML Platform leaders, and broader procurement leaders running Databricks at scale.