Description

Introduction of Data Preparation with ThoughtSpot

Effective data preparation is the foundation of advanced analytics and self-service BI. This course provides a comprehensive guide to data preparation in ThoughtSpot, covering data integration, transformation, cleaning, and modeling techniques. Participants will learn how to optimize their data for AI-powered search and analytics, enabling faster insights and decision-making.

Prerequisites

• Basic understanding of data analytics concepts
• Familiarity with SQL and relational databases (optional)
• No prior ThoughtSpot experience required

Table of Contents

1. Introduction to Data Preparation in ThoughtSpot

1.1 What is Data Preparation?
1.2 Role of Data in Self-Service BI and Advanced Analytics
1.3 Overview of ThoughtSpot’s Data Preparation Capabilities

2. Connecting to Data Sources

2.1 Supported Data Sources (Cloud, On-Premises, Databases, Files)
2.2 Setting Up Data Connections in ThoughtSpot
2.3 Data Import and Synchronization Best Practices

3. Data Cleaning and Transformation

3.1 Identifying and Handling Missing Data
3.2 Data Standardization and Formatting
3.3 Deduplication and Data Quality Best Practices

4. Data Modeling and Schema Design

4.1 Understanding Data Relationships in ThoughtSpot
4.2 Creating Joins, Keys, and Indexing Strategies
4.3 Optimizing Schema for Faster Query Performance

5. Using ThoughtSpot DataFlow for ETL Processes

5.1 Introduction to DataFlow and Data Pipelines
5.2 Data Transformation Using SQL and Custom Scripts
5.3 Automating ETL Workflows for Scalable Analytics

6. Columnar Storage and Data Performance Optimization

6.1 How ThoughtSpot Handles Large Data Volumes
6.2 Indexing Strategies for Faster Searches
6.3 Partitioning and Caching Techniques

7. Implementing Advanced Analytics in ThoughtSpot

7.1 Building Searchable Data Models
7.2 Enabling AI-Driven Insights and Automated Analysis
7.3 Hands-On: Preparing Data for Predictive Analytics(Ref: Business Analytics Foundations: Data-Driven Decision Making)

8. ThoughtSpot Integration with BI and AI Tools

8.1 Exporting and Sharing Data with Other BI Platforms
8.2 Connecting ThoughtSpot with AI/ML Models
8.3 Using APIs for Data Enrichment and Automation

9. Data Security and Governance in ThoughtSpot

9.1 Role-Based Access Control (RBAC)
9.2 Data Masking and Compliance Measures
9.3 Auditing and Monitoring Data Usage

10. Case Studies and Real-World Applications

10.1 Data Preparation for Sales and Marketing Analytics
10.2 Financial Data Modeling for Risk Analysis
10.3 Supply Chain Optimization with Advanced Data Preparation

Conclusion

This training equips participants with hands-on experience in preparing data for analytics in ThoughtSpot. By the end of the course, users will be able to clean, transform, model, and optimize data for seamless self-service analytics and AI-driven insights.

Reference