You're reading from Microsoft 365 and SharePoint Online Cookbook Over 100 practical recipes to help you get the most out of Office 365 and SharePoint Online

Product type Paperback

Published in Jun 2020

Publisher Packt

ISBN-13 9781838646677

Length 810 pages

Edition 1st Edition

Tools

Office 365

Concepts

Project Management

Authors (2):

Gaurav Mahajan

Sudeep Ghatak

View More author details

Table of Contents (19) Chapters

Preface

1. Section 1: AWS Data Engineering Concepts and Trends

2. Chapter 1: An Introduction to Data Engineering FREE CHAPTER

3. Chapter 2: Data Management Architectures for Analytics

4. Chapter 3: The AWS Data Engineer's Toolkit

5. Chapter 4: Data Cataloging, Security, and Governance

6. Section 2: Architecting and Implementing Data Lakes and Data Lake Houses

7. Chapter 5: Architecting Data Engineering Pipelines

8. Chapter 6: Ingesting Batch and Streaming Data

9. Chapter 7: Transforming Data to Optimize for Analytics

10. Chapter 8: Identifying and Enabling Data Consumers

11. Chapter 9: Loading Data into a Data Mart

12. Chapter 10: Orchestrating the Data Pipeline

13. Section 3: The Bigger Picture: Data Analytics, Data Visualization, and Machine Learning

14. Chapter 11: Ad Hoc Queries with Amazon Athena

15. Chapter 12: Visualizing Data with Amazon QuickSight

16. Chapter 13: Enabling Artificial Intelligence and Machine Learning

17. Chapter 14: Wrapping Up the First Part of Your Learning Journey

18. Other Books You May Enjoy

Chapter 12: Visualizing Data with Amazon QuickSight

In Chapter 11, Ad Hoc Queries with Amazon Athena, we looked at how Amazon Athena enables data analysts to run ad hoc queries against data in the data lake using the power of SQL. And while SQL is an extremely powerful tool for querying large datasets, often, the quickest way to understand a summary of a dataset is to visualize the data in graphs and dashboards.

In this chapter, we will do a deeper dive into Amazon QuickSight, a Business Intelligence (BI) tool that enables the creation of rich visualizations that summarize data, with the ability to filter and drill down into datasets in numerous ways.

In smaller organizations, a data engineer may be tasked with setting up and configuring a BI tool that data consumers can use. Things may be different in larger organizations, where there may be a dedicated team to manage the BI system. However, it is still important for a data engineer to understand how these systems work, as...