Book Image

Business Intelligence with Databricks SQL

By : Vihag Gupta
Book Image

Business Intelligence with Databricks SQL

By: Vihag Gupta

Overview of this book

In this new era of data platform system design, data lakes and data warehouses are giving way to the lakehouse – a new type of data platform system that aims to unify all data analytics into a single platform. Databricks, with its Databricks SQL product suite, is the hottest lakehouse platform out there, harnessing the power of Apache Spark™, Delta Lake, and other innovations to enable data warehousing capabilities on the lakehouse with data lake economics. This book is a comprehensive hands-on guide that helps you explore all the advanced features, use cases, and technology components of Databricks SQL. You’ll start with the lakehouse architecture fundamentals and understand how Databricks SQL fits into it. The book then shows you how to use the platform, from exploring data, executing queries, building reports, and using dashboards through to learning the administrative aspects of the lakehouse – data security, governance, and management of the computational power of the lakehouse. You’ll also delve into the core technology enablers of Databricks SQL – Delta Lake and Photon. Finally, you’ll get hands-on with advanced SQL commands for ingesting data and maintaining the lakehouse. By the end of this book, you’ll have mastered Databricks SQL and be able to deploy and deliver fast, scalable business intelligence on the lakehouse.
Table of Contents (21 chapters)
1
Part 1: Databricks SQL on the Lakehouse
9
Part 2: Internals of Databricks SQL
13
Part 3: Databricks SQL Commands
16
Part 4: TPC-DS, Experiments, and Frequently Asked Questions

Warehouse on the Lakehouse

Traditional data warehousing implementations are comprised of different components such as a staging area, operational data store, enterprise data warehouse, and data marts. Depending on the implementation of the system, these components may or may not be transparent to the user. One of the biggest mental leaps you must take when adopting the Lakehouse is how to translate these components to the Lakehouse.

In this chapter, we will learn how to design and implement these components on the Lakehouse using Delta Lake features and ETL design patterns of the Lakehouse.

In this chapter, we will cover the following topics:

  • Organizing data on the Lakehouse
  • Implementing data modeling techniques

The primary audience of this chapter is database administrators and data engineers who will be responsible for designing and implementing the data models corresponding to the different architectural components.