Module 1: Introduction to Teradata Vantage

• Overview of Teradata Vantage: Understanding Teradata Vantage as an integrated data analytics platform.
• Teradata Vantage Architecture:
  • Teradata Vantage on-premises vs. cloud.
  • Components of Vantage (e.g., database engine, query engine, analytics engine).
• Features and Capabilities: Advanced analytics, AI, machine learning, and data lake integration.

Module 2: SQL Fundamentals on Teradata Vantage

• SQL Basics: SELECT, INSERT, UPDATE, DELETE queries.
• Teradata SQL Extensions: Specialized SQL functions in Teradata for performance and scalability.
• Working with Tables: Creating, altering, and managing tables, including partitioned tables.
• Joins: INNER, OUTER, and CROSS joins.
• Aggregations and Grouping: Group By, Having, and other aggregation functions.

Module 3: Data Warehousing Concepts

• Teradata Database Architecture: Architecture overview of the Teradata system (AMPs, Parsing Engine, BYNET).
• Data Modeling for Teradata:
  • Star Schema vs Snowflake Schema.
  • Handling large datasets in Teradata using normalization and denormalization.
• Data Distribution:
  • How data is distributed across nodes in Teradata (hashing and primary index).
• Indexing and Partitioning:
  • Primary, secondary, and join indexes.
  • Partitioned Primary Index (PPI) for optimizing query performance.

Module 4: Data Loading and ETL Processes

• Data Load Techniques:
  • FastLoad, MultiLoad, TPT (Teradata Parallel Transporter).
  • Best practices for data loading in Teradata.
• ETL Process: Extract, Transform, and Load workflows for large-scale data pipelines.
• Managing Large Data Volumes: Optimizing load times and managing high-velocity data.

Module 5: Query Performance Optimization

• Teradata Query Optimization:
  • Query planning and execution.
  • Analyzing and improving query performance.
• Execution Plans: Understanding how Teradata executes queries and how to read execution plans.
• Resource Management: Managing system resources effectively with workload management.
• Statistics Collection: Using and managing statistics to improve query performance.

Module 6: Advanced Analytics with Teradata Vantage

• In-Database Analytics:
  • Using Teradata SQL for complex analytics.
  • Built-in analytics functions (e.g., window functions, pattern matching).
• Machine Learning Integration:
  • Teradata Vantage’s integration with tools like Python, R, and SQL for machine learning.
  • Building, training, and deploying machine learning models directly in the database.
• Text and Data Mining: Text analytics features, such as sentiment analysis, pattern discovery, and text classification.
• Teradata Vantage AI: Leveraging Vantage’s AI capabilities for advanced analytics and predictions.

Module 7: Cloud Integration and Data Lakes

• Vantage in the Cloud:
  • Integration of Teradata Vantage with cloud environments (AWS, Microsoft Azure, Google Cloud).
  • Deploying Vantage on cloud platforms and hybrid architectures.
• Data Lake Integration: Managing and analyzing unstructured data from data lakes.
• Data Sharing and Collaboration: Sharing data across different teams and departments using Vantage’s cloud and on-prem solutions.

Module 8: Business Intelligence and Visualization

• Connecting BI Tools to Teradata:
  • Integration with popular business intelligence tools like Tableau, Power BI, and MicroStrategy.
• Building Dashboards and Reports: Using Teradata data for creating business dashboards and reports.
• Data Visualizations: Best practices for visualizing large datasets for decision-making.

Module 9: Security and Compliance

• Teradata Security Features:
  • User management, access control, and encryption.
  • Authentication and authorization in Vantage.
• Compliance and Auditing:
  • Security auditing, monitoring, and ensuring data compliance standards (e.g., GDPR, HIPAA).

Module 10: System Administration and Maintenance

• Teradata System Architecture:
  • Managing system resources, nodes, and clusters.
• Backup and Recovery:
  • Implementing backup strategies for data protection.
  • Disaster recovery (DR) processes.
• System Monitoring and Troubleshooting: Using Teradata tools for performance monitoring, diagnostics, and problem-solving.
• Software Updates and Upgrades: Managing software versions and patching in Teradata systems.