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Business Intelligence with Databricks SQL

Business Intelligence with Databricks SQL

By : Vihag Gupta
4.6 (13)
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Business Intelligence with Databricks SQL

Business Intelligence with Databricks SQL

4.6 (13)
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)
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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 put on the lens of an end user of Databricks SQL – the business analyst or the data analyst – and learned about the features that enable end users to go through their daily workflows.

First, we learned how to build queries and visualizations and how to compose them into usable dashboards. After that, we learned how to put the dashboards to use with various sharing and alerting features. Finally, we learned how to administer and govern all these artifacts. We learned all this while navigating a hands-on example and compiled our very own operational dashboard.

In this chapter, we assumed that the required computation power is available to us to build and run queries and dashboards. In the next chapter, where we will cover SQL Warehouses, we will go behind the scenes and see how this computation power comes about and how to configure it for the best possible end user experience.

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Business Intelligence with Databricks SQL
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