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Effective Business Intelligence with QuickSight

You're reading from   Effective Business Intelligence with QuickSight Boost your business IQ with Amazon QuickSight

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Product type Paperback
Published in Mar 2017
Publisher
ISBN-13 9781786466365
Length 262 pages
Edition 1st Edition
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Author (1):
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Rajesh Nadipalli Rajesh Nadipalli
Author Profile Icon Rajesh Nadipalli
Rajesh Nadipalli
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Table of Contents (9) Chapters Close

Preface 1. A Quick Start to QuickSight FREE CHAPTER 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

Loading Redshift data to QuickSight


In this section, we will look into the data flow path from the US census to QuickSight using a Redshift data store. The source data is obtained from the public site and provides information about household income and population in the USA by zip code. The path to get to QuickSight involves the following steps:

  1. Uploading data to S3.

  2. Creating an AWS Data Pipeline to load data from S3 to Redshift.

  3. Loading data from Redshift to QuickSight.

Pre-requisites

The following are the pre-requisites to load data from Redshift to QuickSight:

  • Must have a Redshift instance created.

  • Data file must be a CSV. It cannot contain a header in the data file.

  • You must have a database username and password that can connect to the database from QuickSight with the SELECT permission on some system tables so that QuickSight can estimate the table size. These tables are pg_stats, pg_class, and pg_namespace.

Uploading data to S3

For this demonstration, we will use the file USACensusSalarybyZip...

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