Many enterprises struggle to formulate a data architecture that supports their current and future analytics needs. Should they build a data lake or a data warehouse—or some combination of the two? What are the advantages and disadvantages of these two architectural paradigms, and which types of analytics applications are best served by each of them?
This ebook discusses the unique qualities of data warehouses and data lakes, reviews their key differences, and explains how you can establish a single cloud data platform that supports both approaches, simplifying your overall data environment. Discover how to:
- Solve common business and technology challenges
- Create an extensible data architecture with Snowflake
- Use Snowflake to augment an existing data lake