ThoughtSpot Boot Camp

Part 1: Introduction

1. Cloud Analytics Overview
   1. What is it and how does it work?
2. Dashboards vs. Modern Cloud Solutions
   1. Pros and cons of dashboards and modern cloud solutions
   2. Preview "Dashboards are Dead" ThoughtSpot e-book
3. ThoughtSpot Overview
4. What is ThoughtSpot?
   1. Mission and vision
      1. ThoughtSpot's company-specific terminology
      2. Pricing and licensing
      3. Trust Center (ThoughtSpot's cloud security and governance controls) introduction
      4. ThoughtSpot developers platform (ThoughtSpot Everywhere) introduction
      5. ThoughtSpot Community introduction
      6. ThoughtSpot U introduction
   2. ThoughtSpot solutions for clients
5. ThoughtSpot Products
   1. Search
   2. Visualize
   3. Auto-analyze
   4. Mobile (extra demo: mobile application tour)
   5. Connect
   6. Operationalize
   7. Embed
   8. Govern and secure
   9. Demo: ThoughtSpot products overview (more focused on search, visualize, auto-analyze, connect and operationalize).
6. Course Prerequisites Before Moving on to Part 2
   1. Prerequisites overview
7. Exercise:
   1. Create a Google Drive account (for use with Google Sheets in part 6).
      1. Check demo data availability in the data warehouse and run a test query provided by the instructor.
   2. Access a data warehouse with demo login credentials provided by the instructor.

Part 2: Set up Your Data in ThoughtSpot

For BI and data analysts, the first step in working with ThoughtSpot is setting up a data connection. Data can either be uploaded, or a data connection can be made.

1. Demo: Introduce sample CSV file and sample data in the database.
2. Upload data with a CSV file
   1. Demo: Upload sample data with a CSV file.
3. Connect to a data source
4. What is ThoughtSpot Embrace?
   1. If data is stored in data warehouses, the data can be connected through ThoughtSpot Embrace
   2. Connecting data with Embrace
5. How to set up your data connection in ThoughtSpot
   1. Discuss cloud data warehouses supported by ThoughtSpot: Snowflake, Amazon Redshift, Google BigQuery, Azure Synapse, Oracle ADW, Starburst, and Databricks
   2. Demo: Connect to a data source with sample data—select an external database to use throughout the course (e.g., Snowflake).
   3. Exercise: Set up a data connection to the selected external database.

Part 3: Prepare Your Data for ThoughtSpot

1. Create Table Joins
   1. Set joins on the database level
   2. Set joins in ThoughtSpot
   3. Exercise: Create joins for the sample data.
2. Create Worksheets
3. ThoughtSpot use cases
   1. The importance of good use cases (first formulate a good use case, and then design a worksheet to support it)
      1. Exercise: Formulate a good use case.
      2. Advantages of worksheets over directly querying the data
      3. Worksheet design
      4. How to create a worksheet through data setup
      5. How to create a worksheet manually
      6. Exercise: Create a worksheet based on the (example) use case.
   2. Characteristics of a good use case
   3. Demo: Example use case.
4. Create formulas
   1. Formula function reference
   2. Row-wise formulas
   3. Aggregation formulas
   4. Exercise: Create formulas using sample data.

Part 4: Search Your Data to Create New Insights

1. NLQ Overview
   1. What is NLQ and how does it work?
   2. Demo: NLQ example and corresponding SQL query.
2. Search Answers: Existing Answers
   1. Demo: Navigate Search Answers default page.
3. Working with answers
   1. Search within existing answers
      1. Stats and trends for search on answers pinboard
   2. Save answers
   3. Favorite answers
   4. Disable answer search for specific worksheets
4. Search Data: Creating Your Own Searches from Raw Data
   1. Demo: Navigate to the Search Data page and choose sources.
   2. ThoughtSpot's keyword reference list overview
5. Master basic searches: How to perform NLQ and refine your search
   1. Formulate an NLQ on sample data in ThoughtSpot
      1. Drilldown
   2. Save answers using sample data
   3. Filter your data
6. Query details
   1. Query visualizer
      1. Query SQL
7. SearchIQ Overview
8. What is SearchIQ and how does it work?
   1. SearchIQ understands more natural, speech-like language than the original ThoughtSpot search. It's currently in beta and only available in English.
   2. Demo: Search IQ introduction and example. Compare original search and SearchIQ questions.
9. Creating Search Assist Example Queries
   1. What is search assist?
   2. How to create search assist example queries
10. Exercise: Practice NLQ by answering five to 10 questions about the sample data (e.g., how many jackets were sold between 2017 and 2019, what is the monthly revenue per product, etc.) and save your answers.

Part 5: Visualize Your Data and Get AI-Driven Analytics

1. Custom Visualization
2. ThoughtSpot charts overview
   1. Requirements for chart visualization
   2. Types of charts
3. Narrow down on common graphs (column, bar, line, scatter) and also geo maps
   1. Geo map reference
   2. Adjusting chart aspects (such as axes, legend, color, etc.)
   3. Demo: Review custom visualization with different chart types (column, bar, line, scatter, geo) and scenarios for when to use them.
4. Pinboards
   1. What is a pinboard and how does it work?
   2. How to create a pinboard
   3. Pinboard actions
5. SpotIQ Analysis
   1. What is SpotIQ and how does it work?
   2. SpotIQ from an answer or search
   3. SpotIQ from a pinboard
   4. How to customize SpotIQ analyses
   5. Demo: Review SpotIQ AI-driven analytics and how to customize it.
6. Exercise: Create a custom visualization—choose appropriate graph types to answer questions—and explore SpotIQ analysis.
7. Exercise: Create a pinboard from multiple saved answers and explore SpotIQ analysis.

Part 6: Operationalize Your Analytics

1. Move and Share Your Work
2. Scriptability feature
   1. Prerequisites
      1. How to export, import, and migrate data
      2. SpotApps overview
      3. ThoughtSpot Modeling Language (TML) overview
   2. Workflows
3. Push Insights to Business Applications
4. Use Seekwell to connect your data warehouse to business apps (Google Sheets, Excel, Slack, etc.)
   1. Use pre-built connectors
      1. Publish models from your warehouse automatically
   2. Map SQL columns to fields in business apps
5. Demo:
   1. Perform an NLQ search and use the generated SQL to pull the data from the cloud warehouse
   2. Then sync it to a business application (Google Sheets) using SeekWell.
6. Exercise: Send answer data (from the exercises in part 4 and 5) to Google Sheets (or other business apps).

Professionals who may benefit from this ThoughtSpot training include:

• Business Intelligence Specialists
• Data Analysts
• Database Administrators
• Project Managers
• Business Analysts
• Digital Marketers
• IT Specialists
• IT Managers/IT Directors
• Anyone responsible for implementing BI

• Set up your data in ThoughtSpot by either uploading a file or connecting to a cloud data warehouse,
• Search your data using Natural Language Query (NLQ),
• Make custom visualizations for your data,
• Create worksheets and pinboards (live dashboards) with your data,
• Use SpotIQ to get AI-driven analyses and discover underlying questions about your data, and
• Operationalize your data by pushing your data insights to business apps.