Fundamentals of Enterprise Data Management Systems

Summary

Evaluate options for data storage and organization when designing big data analytics systems.

Description

Whether your organization is moving to the cloud for the first time or reevaluating its current approach, making decisions about the technology used when storing your data can have huge implications for costs and performance in downstream analytics. As a platform focused on computation and analytics, Databricks seeks to help our customers make choices that unlock new opportunities, reduce redundancies, and connect data teams. In this course, you’ll start by exploring the characteristics of data lakes, and data warehouses, two popular data storage technologies. Then, you’ll learn about the Lakehouse, a new data storage system invented and made popular by Databricks.

Learning objectives

  • Describe the strengths and limitations of data lakes, related to data storage.

  • Describe the strengths and limitations of data warehouses, related to data storage.

  • Contrast data lake and data warehouse characteristics.

  • Compare the features of a Lakehouse to the features of popular data storage management solutions.

Prerequisites

  • Beginning knowledge about the Databricks Unified Data Analytics Platform.

  • We recommend taking the courses: Fundamentals of Big Data and Fundamentals of the Databricks Lakehouse Platform.

Learning path

  • This course is part of the Business Leader learning path.

Proof of completion

  • Upon 80% completion of this course, you will receive a proof of completion.