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Business Intelligence with Databricks SQL

You're reading from   Business Intelligence with Databricks SQL Concepts, tools, and techniques for scaling business intelligence on the data lakehouse

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Product type Paperback
Published in Sep 2022
Publisher Packt
ISBN-13 9781803235332
Length 348 pages
Edition 1st Edition
Languages
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Author (1):
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Vihag Gupta Vihag Gupta
Author Profile Icon Vihag Gupta
Vihag Gupta
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Table of Contents (21) Chapters Close

Preface 1. Part 1: Databricks SQL on the Lakehouse
2. Chapter 1: Introduction to Databricks FREE CHAPTER 3. Chapter 2: The Databricks Product Suite – A Visual Tour 4. Chapter 3: The Data Catalog 5. Chapter 4: The Security Model 6. Chapter 5: The Workbench 7. Chapter 6: The SQL Warehouses 8. Chapter 7: Using Business Intelligence Tools with Databricks SQL 9. Part 2: Internals of Databricks SQL
10. Chapter 8: The Delta Lake 11. Chapter 9: The Photon Engine 12. Chapter 10: Warehouse on the Lakehouse 13. Part 3: Databricks SQL Commands
14. Chapter 11: SQL Commands – Part 1 15. Chapter 12: SQL Commands – Part 2 16. Part 4: TPC-DS, Experiments, and Frequently Asked Questions
17. Chapter 13: Playing with the TPC-DS Dataset 18. Chapter 14: Ask Me Anything 19. Index 20. Other Books You May Enjoy

Working with queries

In Chapter 2, The Databricks Product Suite – A Visual Tour, in Figure 2.9, we briefly introduced the SQL Editor as the intelligent workbench that is at the center of the end user experience for day-to-day work.

In this section, we’ll look into the capabilities that the SQL Editor brings to the table.

In the previous chapters, we used the SQL Editor to either program the security model or explore the data assets visually. Hence, I’m not going to introduce the basic layout of the page and dive straight into the most important features.

Continuing within the spirit of the previous chapters, let’s start by incorporating another dataset from the bundled databricks-datasets into our data catalog for use in this chapter. Here, we will use the NYC Taxi Trip dataset.

Like the previous chapters, execute the following SQL snippet to register this dataset as a database:

--create the database
CREATE DATABASE nyc_taxi;
--Set nyc_taxi...
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