AWS QuickSight Lab

AWS QuickSight

AWS QuickSight


QuickSight Setup

Click on Sign up for QuickSight

Select Standard, then click on Continue


Input your QuickSight account name and Notification email address

Check Amazon S3 then select the proper bucket you want to share the access permission to AWS QuickSight

Check Amazon S3 Storage Analytics and AWS IoT Analytics
Click on Finish


QuickSight Visualizations


Line Chart & Scatter Plot

AWS QuickSight
Quick Start: Create an Analysis with a Single Visual Using Sample Data


Lab Details

  • Prepare a marketing data set consiting of web application user info gathered from web logs
  • Create an analysis
  • Create a dashboard
  • Understand various visualization types
  • Learn how to operationalize visualizations

Task Details

  1. Download the AWS sample dataset web-and-social-analytics.csv.zip]
  2. Upload the dataset to your S3 bucket
  3. Create a manifest file in order to let the QuickSight connect to the dataset in S3
  4. Analyze and visualize the dataset

Prerequisite


Download the dataset

Download web-and-social-analytics.csv.zip and unzip it.


Upload the dataset to your S3 bucket

Upload the web-and-social-analytics.csv.zip to your S3 bucket. If you don’t have any bucket, then create a bucket.


Copy the object S3 URI


Create a Manifest file

Create a JSON file with the name web-and-social-analytics_manifest.json.
Copy and paste the following JSON code to web-and-social-analytics_manifest.json.
Replace the URIs to your object S3 URI

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{
"fileLocations": [
{
"URIs": [
"s3://aws-labs-bucket/QuickSight/VisualizationServices/web-and-social-analytics.csv"
]
}
],
"globalUploadSettings": {
"format": "CSV",
"delimiter": ",",
"textqualifier": "'",
"containsHeader": "true"
}
}


QuickSight Configuration


Services -> QuickSight


Connect to S3

Click on Datasets on navigation panel


Click on New dataset on the right and top page


Click on S3


  • Data source name: web-and-social-analytics

Click on Upload

Click on the folder icon and select your web-and-social-analytics_manifest.json file, then click on Chooser for Upload

Click on Connect

Click on Edit/Preview data


Edit/Preview data

Click on any column for editing the column name.

Click on Cancel

Click on Add calculated field


Add a calculated field for calculating one or more columns. You can also do it later.

Add name: populated_event

Under the Functions area, double click on ifelse

ifelse SYNTAX
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ifelse(if, then [, if, then ...], else)

Expand Fields

Move your cursor inside the () of ifelse()
Then double click on Events for adding field to function

Type the following expression.
It means if the an event string length is 0, then assign it then value UNKNOWN. Otherwise, keep the original value of the event.

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ifelse(strlen({Events})=0, 'UNKNOWN', {Events})

Click on Save


Now we have the new field populated_event and many UNKNOWN values

Click on Save & visualize on the top and middle page


Line chart
  • Visual types: Line chart
  • X axis:
    • Data (MONTH)
    • New Visitors (SEO)
  • Value: Return vision (Sum)

Click on Date under X axis for aggregate it by Month

Click on the Return visitors (Sum) line for updating the color to red


Scatter plot

Click on Add -> Add visual

  • X axis: Desktop uniques (Sum)
  • Y axis: Mobile uniques (Sum)
  • Group/Color: Data (MONTH)


Filter for Line Chart

Click on Filter on the navigation panel

Click on Create one -> Date

Click on Date filter


Filter type

  • Time range
  • After

Date

  • 2014-01-01

Click on Apply



Filter for Scatter Plot

Click on Scatter plot then click on Create one -> Date


Filter type

  • Time range
  • After

Date

  • 2014-01-01

Click on Apply


Create a Dashboard

Click on Share -> Publish dashboard on the top and right page

  • Publish new dashboard as: Marketing Dashboard

Click Advanced publish options

Scroll down to see more information

Click on Publish dashboard

You can share the dashboard, or click on Xfor exiting


Dashboard console is designed for presenting to the users.

The users can also interact with the dashboard

Line Chart - Drill down to WEEK

Line Chart - Drill up to MONTH

Scatter Plot - Drill down to WEEK

Scatter Plot - Drill up to MONTH


QuickSight Athena


Athena in Analysis and Visualization Solution


QuickSight Kinesis


Kinesis Data Analytics


QuickSight Redshift


Redshift


Redshift Spectrum


QuickSight Third-Party Data Sources

GitHub Repository

Creating a Data Source and Data Set from SaaS Sources


Lab Details

  • Build an analysis using GitHub as a data source
    • Requires you to authorize QuickSight to gain access to your GitHub account

QuickSight Configuration

Services -> QuickSight


Connect to GitHub

Click on Datasets on navigation panel


Click on New dataset on the right and top page


Click on GitHub


  • Data source name: your github link

Click on Validate connection

Click on Authorize QuickSight-IAD

Confirm your password

Choose Repository then click on Edit/Preview data


Edit/Preview data

You can see all of you repositories.

Click on Save & visualize on the top and middle page


AutoGraph
  • Visual types: AutoGraph
  • X axis: CreateAt
  • Color: Name

It gives us a scatter plot.


PieChart
  • Visual types: PieChart
  • X axis: CreateAt
  • Value: Name (Count)

Drill up to WEEK

Different frequency provides different viewpoints


Scatter Plot
  • Visual types: Scatter Plot
  • X axis: Name (Count)
  • Y axis: Description (Count)
  • Group/Color: PushedAt (MONTH)
  • Size: CreateAt (Count)


Word Cloud
  • Visual types: Word Cloud
  • Group by: CreatedAt
  • Size: PushedAt (Count)


Twitter

Lab Details

  • Build an analysis using Twitter as a data source
    • Requires you to authorize QuickSight to gain access to your Twitter account

QuickSight Configuration

Services -> QuickSight


Connect to Twitter

Click on Datasets on navigation panel


Click on New dataset on the right and top page


Click on Twitter


  • Data source name: your Twitter link
  • Query: one keyword of your tweets
  • Maximum rows: 100

Click on Validate connection

Click on Authorize Authorize app

Choose Twitt then click on Edit/Preview data


Edit/Preview data

You can see many interesting information like UserName, RetweetCount, etc.

Click on Save & visualize on the top and middle page


WordCloud
  • Visual types: WordCloud
  • Group/Color: Text
  • Size: RetweetCount (Sum)

You can reorder the Text by RetweetCount (Sum)

Put your cursor on any Text to see the full content.


Line Chart
  • Visual types: Line Chart
  • X axis: RetweetCount
  • Value: UserTwitterCount (Count)


QuickSight Embedded

Embedding Overview


Step 1: In Amazon QuickSight, create your dashboards and whitelist your domains

Services -> QuickSight

Embed interactive dashboards in your application with Amazon QuickSight


Create a QuickSight group through AWS CLI.

AWS CLI
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aws quicksight create-group --aws-account-id 542892269888 --namespace default --group-name zacks.one 

Click on Share, then you can see the group you just created

Click on Share

Click on Save as

Click on Confirm

Exit the session

Click on Manage QuickSight

Click on Domains and Embedding

Add your domain. https is required.


Step 2: In your AWS account, set up permissions for embedded viewers

To be continued.