What is Teradata?: Overview of Teradata as a data warehouse and analytics platform, its features, and its benefits.
Architecture: Understanding Teradata’s architecture, including its parallel processing capabilities, and how it supports large-scale data warehousing.
Use Cases: Common scenarios where Teradata is used, such as enterprise data warehousing, business intelligence, and big data analytics.
2. Teradata Environment and Installation
Installation: Steps for installing Teradata, including Teradata Database and Teradata Tools and Utilities (TTU).
Configuration: Configuring Teradata for optimal performance, including setting up nodes and managing resources.
Teradata Studio: Using Teradata Studio and other client tools for database management and development.
3. Data Modeling and Schema Design
Data Modeling: Concepts of data modeling, including star schema, snowflake schema, and normalization.
Schema Design: Designing efficient schemas in Teradata to support large-scale data warehousing and analytics.
Table Design: Creating and managing tables, including choosing appropriate data types, indexing strategies, and partitioning.
4. SQL Programming in Teradata
Basic SQL Queries: Writing basic SQL queries for data retrieval, insertion, updating, and deletion.
Advanced SQL Features: Using advanced SQL features such as complex joins, subqueries, and window functions.
Stored Procedures and Macros: Creating and managing stored procedures, macros, and user-defined functions to encapsulate business logic.
5. Data Loading and Extraction
Data Loading: Techniques for loading data into Teradata using tools like Teradata Parallel Transporter (TPT), FastLoad, MultiLoad, and SQL*Loader.
Data Extraction: Extracting data from Teradata and integrating it with other systems or tools.
Data Transformation: Using SQL and other tools to transform data during loading and extraction processes.
6. Performance Tuning and Optimization
Query Optimization: Techniques for optimizing SQL queries and understanding Teradata’s query execution plans.
Resource Management: Managing and configuring Teradata resources, including workload management and system performance.
Indexing and Partitioning: Using indexing and partitioning strategies to enhance performance and data retrieval efficiency.
7. Data Warehousing and Analytics
Data Warehousing Concepts: Understanding data warehousing principles, including data integration, ETL (Extract, Transform, Load) processes, and data marts.
Advanced Analytics: Performing advanced analytics using Teradata tools and SQL, including statistical analysis, data mining, and predictive modeling.
Business Intelligence: Integrating Teradata with business intelligence (BI) tools for reporting, visualization, and decision-making.
8. Security and User Management
User Management: Creating and managing users, roles, and permissions in Teradata.
Security Best Practices: Implementing security measures to protect data, including encryption, authentication, and access control.
Compliance: Ensuring compliance with data governance and regulatory requirements.
9. Backup and Recovery
Backup Strategies: Implementing backup strategies to ensure data integrity and availability.
Recovery Processes: Performing recovery operations in case of data loss or system failure.
Disaster Recovery: Planning and implementing disaster recovery strategies to safeguard against data loss.
10. Integration with Other Systems
ETL Integration: Integrating Teradata with ETL tools and processes for data extraction, transformation, and loading.
APIs and Connectors: Using APIs and connectors to integrate Teradata with other applications and systems.
Data Federation: Federating data from multiple sources and integrating it with Teradata for comprehensive analysis.
11. Real-World Use Cases and Best Practices
Case Studies: Exploring real-world case studies and examples of successful Teradata implementations.
Best Practices: Implementing best practices for database design, performance optimization, and data management in Teradata.
12. Future Trends and Developments
New Features: Staying updated with the latest features and enhancements in Teradata.
Emerging Trends: Understanding emerging trends in data warehousing, big data, and analytics, and how Teradata is evolving to address these trends.
Course Format
Lectures and Readings: Comprehensive theoretical content covering Teradata’s features and capabilities.
Hands-On Labs: Practical exercises to set up, configure, and manage Teradata databases.
Assignments and Projects: Real-world projects to apply knowledge and skills in practical scenarios.
Exams and Quizzes: Assessments to test understanding and proficiency with Teradata.
Target Audience
Database Administrators: Professionals managing and optimizing Teradata databases in enterprise environments.
Developers: Individuals building applications and solutions that leverage Teradata for data warehousing and analytics.
Data Analysts and Scientists: Analysts and scientists performing data analysis and generating insights using Teradata.
IT Managers: Managers overseeing the deployment and operation of Teradata data warehousing solutions.
Prerequisites
Basic Database Knowledge: Understanding of fundamental database concepts and principles.
Familiarity with SQL: Basic knowledge of SQL is often beneficial for working with Teradata.
Basic Understanding of Data Warehousing: Familiarity with data warehousing concepts can be helpful.
