AWS QuickSight Lab
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
- Download the AWS sample dataset web-and-social-analytics.csv.zip]
- Upload the dataset to your S3 bucket
- Create a manifest file in order to let the QuickSight connect to the dataset in S3
- 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
1 | { |
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
1 | 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.
1 | 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 X
for 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
QuickSight Redshift
Redshift
Redshift Spectrum
QuickSight Third-Party Data Sources
GitHub Repository
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)
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
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.
1 | 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.