Data Warehouse to Data Lakehouse Migration Playbook

Organizations find it challenging to maintain cloud data warehouses due to data lock-in, complex ETL processes involving data copying, and slow time to insight, which leads to a high total cost of ownership. The data lakehouse offers a modern approach to data architecture by combining the flexibility and scalability of a data lake with the data management and analytical capabilities of a data warehouse, all while standardizing on an open architecture.

In a recent survey of 500 data leaders and practitioners, 69% of organizations predict they will be running a data lakehouse within the next 3 years. The challenge lies in the limited options available that minimize risk during the migration process and unlock use cases that align with the business's shared OKRs.

However, by modernizing to an open data lakehouse with Dremio, organizations can mitigate these risks. Dremio provides a unified lakehouse platform that offers self-service analytics capabilities from day one using a phased migration approach.

In this migration playbook, you will learn:

How Dremio’s open data lakehouse architecture simplifies data architecture while eliminating the need for data warehouses and BI cubes.
A step-by-step guide on how to transition from cloud data warehouses to an open data lakehouse.
An understanding of Dremio’s approach to self-service analytics on the lakehouse using zero-ETL and Git for Data.

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Getting Started with Dremio

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