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

Summary

In this chapter, we deviated from our usual personas of data analysts and database administrators. Instead, we put on the hat of data engineers who are responsible for delivering data to analysts and administrators. Data engineers are wholly responsible for optimizing the data layout on the Lakehouse so that data analysts get the best possible query experience.

That said, we saw how the inputs of data analysts will be integral to getting the data layout correct. Inputs on query-filtering patterns, ordering of data columns, and frequency of optimizations are required for data engineers to make the best decisions.

In this chapter, we learned how Delta Lake is the storage layer for Databricks SQL. We learned how it provides the best out-of-the-box query experience. We also learned about additional features in Delta Lake that can elevate query performance even more. Finally, we discussed the internal workings of Delta Lake and how it enables all the features that Delta Lake...