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

Implementing data modeling techniques

In this section, we will look at the layers of the Medallion architecture. We will discuss the design considerations for the layers, possible data modeling techniques to employ, and how to apply Delta Lake features.

Consider the airlines dataset example that we have been working on throughout this book. Let’s extend that example here to visualize how the various layers can be brought to life on the Lakehouse.

The bronze layer

As we discussed in the previous section, the bronze layer is an as-is replica of source systems and hence the data models will follow that of source systems. Also, the bronze layer tables should ideally be in Delta format for optimal near-real-time query experience and data versioning.

A typical airlines system will contain source systems for functions such as booking, ticketing, check-in, flights, loyalty, and more. Each source system will contain a host of tables.

Consider the following diagram:

...