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.

Transcript

1. Introduction to Amazon QuickSight a fast, cloud-powered business intelligence service that makes it easy to deliver insights to everyone in your organization
4. How it works
5. How it works (cont.)
6. Data Sources ✓ File ✓ CSV, JSON, PARQUET, TSV, XLSX, CLF, ELF ✓ Salesforce ✓ S3 Analytics ✓ S3 ✓ Athena ✓ MySQL ✓ PostgreSQL ✓ SQL Server ✓ etc.
7. 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
8. 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
10. 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
12. 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
13. 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.
14. 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
15. 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
16. Demo Creating an interactive dashboard step-by-step
20. Data Model
21. Loading the data • Click on New Analysis › New Dataset
22. 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.
23. Data - Sales • Data must be prepared before loading to Quicksight
24. Loading the data (cont.) • Upload a file (.xlsx) • Then Visualize
25. Amazon QuickSight
26. Create visualization • Key Performance Indicators (KPIs) • Click the KPI Visual Type • Drag “Sales” field to Value
27. 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
28. 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
29. 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
30. Create visualization (cont.) • Customizing your visual • Chart Size, Axes size • Chart Colors
31. 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
32. 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
33. Publish your dashboard
34. Your turn!