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Introduction to Amazon Quicksight - AWS Meetup

Introduction to Amazon Quicksight - AWS Meetup

This slide deck introduces the concept of Amazon Quicksight as a Business Intelligence tool and how QuickSight lets you easily create and publish interactive BI dashboards that include Machine Learning-powered insights as well as its other features.

Kyle Escosia

March 19, 2021
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  1. Introduction to Amazon QuickSight a fast, cloud-powered business intelligence service

    that makes it easy to deliver insights to everyone in your organization
  2. Data Sources ✓ File ✓ CSV, JSON, PARQUET, TSV, XLSX,

    CLF, ELF ✓ Salesforce ✓ S3 Analytics ✓ S3 ✓ Athena ✓ MySQL ✓ PostgreSQL ✓ SQL Server ✓ etc.
  3. Innovations • Easy exploration of AWS data • Fast insights

    with SPICE (Super-fast, Parallel, In-memory, Calculation Engine) • Intuitive visualizations and transitions with AutoGraph • Native mobile experience • Secure sharing and collaboration through StoryBoards
  4. Fast insights with SPICE • Super-fast, Parallel, In-memory optimized, Calculation

    Engine • 2 to 4x compression columnar data • Compiled queries with machine code generation • Rich calculations • Very fast response time to queries • Fully managed – No hardware or software to license
  5. Tell a story with your data • Capture the critical

    snapshot of analysis • •Build a sequence of analysis • Share it securely • Enable interactive exploration • Very fast response
  6. Three Powerful New Features ML Anomaly Detection Uncover hidden insights

    by continuously analyzing across billions of data points. ML Forecasting Predict key business metrics with point and click simplicity Auto Narratives Tell the story of your data in plain language narratives
  7. ML Anomaly Detection • Discover hidden trends and outliers •

    Anomaly detection enables you to get deep insights that are often buried in the aggregates and not scalable with manual analysis • Schedule automatic anomaly detection jobs across billions of metrics.
  8. ML Forecasting • QuickSight’s built-in algorithms make it easy for

    anyone to use ML that learns from your data patterns to provide you with accurate predictions based on historical trends. • Use ML-powered Forecasting to accurately predict your business metrics, and perform interactive what-if analysis with point-and- click simplicity
  9. Auto Narratives • QuickSight can automatically generate natural language narratives

    that can be woven into your dashboards and reports to provide deeper context for users • Use customized calculations, and custom formatting that allow you to control the story you present to your users
  10. Loading the data (cont.) • Supported data sources: o File

    o CSV, JSON, PARQUET, TSV, XLSX, CLF, ELF o Salesforce o S3 Analytics o S3 o Athena o MySQL o PostgreSQL o SQL Server o etc.
  11. Create visualization • Key Performance Indicators (KPIs) • Click the

    KPI Visual Type • Drag “Sales” field to Value
  12. Create visualization (cont.) • Add another visual • At the

    top-left corner of the screen, click Add visual • Create a Line Graph • Choose line in the visual type • Drag Order Date to X-axis • Drag Sales to Value
  13. Create visualization (cont.) • Formatting the x-axis • In the

    Field wells pane, move to X-axis and click the drop down button • Aggregate • Month • Formatting the Sales as Currency • In the Field wells pane, move to Value and click the drop down button • Show as • Currency
  14. Create visualization (cont.) • Adding Filters • Top 5 Sales

    by Product • Create a new graph, this time a horizontal bar graph • Navigate to Filter in the left panel • Create a filter for Product Name • In the created filter, change the filter to Top and bottom filter • Show top = 5 • By = Sales (Sum) • Click Apply
  15. Making the graphs interactive • Adding Parameters • In the

    left panel, navigate to Parameters to create a new one • Input Name • Click on ‘Set a dynamic default’ • Select dataset • User name column • Default value column • Click the drop-down button and select ‘Add control’ • Input • Display Name • Style = drop down • Values = Link to a data set field • Select a data set • Select column
  16. Making the graphs interactive (cont.) • This will add a

    new panel below the Field wells • However, this is not interactive yet • We need to add another filter to all the visuals • Click on any visual • Create a filter for State • Make sure to select All Visuals • Filter type = Custom filter • Tick Use parameters • Choose your created parameters