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Teredata

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Teredata

Teredata

Duration
45 Hours

Course Description

                     A Teradata course typically covers the fundamentals of the Teradata database system, including its architecture, data warehousing principles, and advanced SQL techniques. It also delves into data loading, performance tuning, and data protection strategies within the Teradata environment. The course aims to equip participants with the skills to manage and analyze large datasets using Teradata, making it suitable for developers, data analysts, and database administrators. 

Course Outline For Teredata

Introduction to Teradata:

  • What is Teradata and why it's used?
  • Comparison of Teradata with other Relational Database Management Systems (RDBMS).
  • History and versions of Teradata.
  • Teradata architecture and its components (e.g., Parsing Engine, AMP, BYNET).
  • How components interact and handle data storage and retrieval.
  • Teradata ecosystem and its connection to other tools.
  • Tools like Teradata Studio and Teradata SQL Assistant.

Teradata SQL:

  • Fundamentals of SQL commands, operators, and functions.
  • Data Definition Language (DDL) statements (CREATE, ALTER, DROP).
  • Data Manipulation Language (DML) statements (INSERT, DELETE, UPDATE).
  • Data Control Language (DCL) statements (GRANT, REVOKE).
  • Advanced SQL techniques like joins, subqueries, OLAP functions, and handling large datasets efficiently.
  • Developing advanced SQL queries and optimizing query performance for large datasets.
  1. Data Protection and Management:
  • Transaction management techniques and data protection mechanisms.
  • Understanding data protection features like fallback tables, clustering, journaling, and standby nodes.
  • Ensuring data integrity and recovery in Teradata environments.
  • Implementing robust security measures and compliance protocols for Teradata databases.
  • Working with the Teradata Data Dictionary.

Teradata Utilities and Tools:

  • Application utilities for importing and exporting data.
  • FastLoad and MultiLoad utilities for data loading.
  • BTEQ scripts for submitting SQL queries.
  • FastExport and TPT (Teradata Parallel Transporter) for data exporting and manipulation.
  • Managing and optimizing data loading processes.

Performance Tuning and Optimization:

  • Identifying and resolving performance bottlenecks.
  • Using performance monitoring tools like PMON.
  • Collecting statistics to improve query performance.
  • Implementing best practices for performance tuning and optimization.

Advanced Topics:

  • Workload management and parallel data extensions.
  • Working with advanced database objects like views, macros, stored procedures, and triggers.
  • Integration with cloud platforms like AWS, Azure, and Google Cloud.
  • Utilizing Teradata Vantage features, including analytics engines, machine learning, and graph capabilities. 
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