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Vihag Gupta - Business Intelligence with Databricks SQL: Concepts, tools, and techniques for scaling business intelligence on the data lakehouse

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Vihag Gupta Business Intelligence with Databricks SQL: Concepts, tools, and techniques for scaling business intelligence on the data lakehouse
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Master critical skills needed to deploy and use Databricks SQL and elevate your BI from the warehouse to the lakehouse with confidence

Key Features
  • Learn about business intelligence on the lakehouse with features and functions of Databricks SQL
  • Make the most of Databricks SQL by getting to grips with the enablers of its data warehousing capabilities
  • A unique approach to teaching concepts and techniques with follow-along scenarios on real datasets
Book Description

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. Youll 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. Youll also delve into the core technology enablers of Databricks SQL Delta Lake and Photon. Finally, youll get hands-on with advanced SQL commands for ingesting data and maintaining the lakehouse.

By the end of this book, youll have mastered Databricks SQL and be able to deploy and deliver fast, scalable business intelligence on the lakehouse.

What you will learn
  • Understand how Databricks SQL fits into the Databricks Lakehouse Platform
  • Perform everyday analytics with Databricks SQL Workbench and business intelligence tools
  • Organize and catalog your data assets
  • Program the data security model to protect and govern your data
  • Tune SQL warehouses (computing clusters) for optimal query experience
  • Tune the Delta Lake storage format for maximum query performance
  • Deliver extreme performance with the Photon query execution engine
  • Implement advanced data ingestion patterns with Databricks SQL
Who this book is for

This book is for business intelligence practitioners, data warehouse administrators, and data engineers who are new to Databrick SQL and want to learn how to deliver high-quality insights unhindered by the scale of data or infrastructure. This book is also for anyone looking to study the advanced technologies that power Databricks SQL. Basic knowledge of data warehouses, SQL-based analytics, and ETL processes is recommended to effectively learn the concepts introduced in this book and appreciate the innovation behind the platform.

Table of Contents
  1. Introduction to Databricks
  2. The Databricks Product Suite A Visual Tour
  3. The Data Catalog
  4. The Security Model
  5. The Workbench
  6. The SQL Warehouses
  7. Using Business Intelligence Tools with Databricks SQL
  8. The Delta Lake
  9. The Photon Engine
  10. Warehouse on the Lakehouse
  11. SQL Commands Part 1
  12. SQL Commands Part 2
  13. Playing with the TPC-DS Dataset
  14. Ask Me Anything

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Business Intelligence with Databricks SQL Concepts tools and techniques for - photo 1
Business Intelligence with Databricks SQL

Concepts, tools, and techniques for scaling business intelligence on the data lakehouse

Vihag Gupta

BIRMINGHAMMUMBAI Business Intelligence with Databricks SQL Copyright 2022 Packt - photo 2

BIRMINGHAMMUMBAI

Business Intelligence with Databricks SQL

Copyright 2022 Packt Publishing

All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.

Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author(s), nor Packt Publishing or its dealers and distributors, will be held liable for any damages caused or alleged to have been caused directly or indirectly by this book.

Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.

Group Product Manager: Reshma Raman

Publishing Product Manager: Heramb Bhavsar

Senior Editor: Nazia Shaikh

Technical Editor: Sweety Pagaria

Copy Editor: Safis Editing

Project Coordinator: Farheen Fathima

Proofreader: Safis Editing

Indexer: Rekha Nair

Production Designer: Vijay Kamble

Marketing Coordinator: Nivedita Singh

First published: September 2022

Production reference: 1260822

Published by Packt Publishing Ltd.

Livery Place

35 Livery Street

Birmingham

B3 2PB, UK.

ISBN 978-1-80323-533-2

www.packt.com

This book came into life with the eternal blessings from Dada Ji & Dadi Ji &Love from Mom, Dad, Utkarsh, Suteja, Toffee & Love for the One who is arriving.

Vihag Gupta

Contributors
About the author

Vihag Gupta is a solutions architect with a specialization in cloud data platform architecture and design. He has a background in data engineering and a professional interest in machine learning. He loves getting hands-on and solving real business problems with technology. He graduated with a degree in information technology from PES University, Bengaluru, in 2011 and earned a degree in information systems management from Carnegie Mellon University, Pittsburgh, in 2016. He has worked at companies including Deloitte Consulting, DataSpark, and Qubole. He currently works at Databricks, helping clients bring their lakehouse platforms for analytics to life.

Originally from Jharkhand, India, Vihag currently lives in Singapore with his wife and dog.

About the reviewers

Jerrold Law currently works at Databricks as a specialist solutions architect, specializing in data engineering and streaming. He helps organizations all over the world to adopt scalable big data processing use cases with the Lakehouse architecture. Prior to Databricks, he worked for Confluent, helping enterprise organizations to enable their real-time streaming use cases as part of the solutions engineering field team.

Ivan Tang is a solutions architect at Databricks, helping enterprises in the ASEAN region in their cloud transformation journey. Previously, he worked with Confluent Professional Services, where he helped enterprises from the APAC region to design, build, operate, and maintain event streaming platforms using Apache Kafka and Confluent. Prior to that, he was wrangling data and building models while being an architect, builder, and user of distributed systems, including Hadoop, Storm, Kafka, and Spark. Prior to that, he worked for Confluent, GIC (Singapores sovereign wealth fund), and other firms.

With over 15 years of experience working as a solutions architect for some of the largest and most innovative companies in the world, including Amazon, Bridgewater, and Bloomberg, Tomasz Kurzydym is a strong supporter and advocate for constant learning, experimentation, and curiosity. His work has taken him from his native country of Poland to the USA and UK, and he now lives with his family in Singapore working for Databricks a data and AI company. In his spare time, Tomasz enjoys traveling, skiing, and photography.

Mahdi Askari is a lead solutions architect at Databricks. He is a software engineer at heart, and has been working in the data and big data space since 2010. He has worked across different industries with customers and prospects using Databricks Lakehouse to derive insight from their data.

Roja Boina is an engineering senior advisor. She provides data-driven solutions to enterprises. She takes pride in her get-it-done attitude. She enjoys defining requirements, designing, developing, testing, and delivering backend applications, and communicating data through visualizations. She is very passionate about being a Women in Tech (WIT) advocate and being a part of WIT communities. Outside of her 9-5, she loves to volunteer for non-profits and mentor fellow women in STEM. She believes in having a growth mindset.

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