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Effective Business Intelligence with QuickSight

You're reading from  Effective Business Intelligence with QuickSight

Product type Book
Published in Mar 2017
Publisher
ISBN-13 9781786466365
Pages 262 pages
Edition 1st Edition
Languages
Author (1):
Rajesh Nadipalli Rajesh Nadipalli
Profile icon Rajesh Nadipalli
Toc

Table of Contents (15) Chapters close

Effective Business Intelligence with QuickSight
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
1. A Quick Start to QuickSight 2. Exploring Any Data 3. SPICE up Your Data 4. Intuitive Visualizations 5. Secure Your Environment 6. QuickSight Mobile 7. Big Data Analytics Mini Project 8. QuickSight Product Shortcomings

Joining data in SPICE


Joining tables is a very common requirement for data analysis and SPICE makes this effort a breeze. To understand this feature, let's go for a real use case. In the Chapter 2, Exploring Any Data, Loading data from Redshift to Quicksight section, we had uploaded USACensusSalarybyZip.csv, which has salary and population information by USA zip code. Now let's upload another file that has mapping of zip codes to USA states and cities and then we will join this with the other dataset in SPICE.

Loading data to Redshift

First we need to load this new file to Redshift as a table. Here are the steps to load the data to Redshift:

  1. Download the data file from this GitHub location: https://github.com/rnadipalli/quicksight/blob/master/sampledata/USAZipCodes.csv.

  2. Upload the file to your S3 bucket.

  3. Create a new AWS data pipeline to upload S3 data to your Redshift cluster and call it USAZIPCODES . You can clone the data pipeline created in the Chapter 2, Exploring Any Data, Creating and...

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