Teradata: desde cero hasta avanzados

• Understanding of relational databases and SQL concepts
• Experience with querying large datasets or working in data environments
• Familiarity with business intelligence or analytics objectives

Audience

• Data analysts and business intelligence professionals
• SQL developers and data engineers
• Technical users managing or optimizing data in Teradata environments

Teradata is a highly scalable database platform designed to manage large volumes of data and enable complex analytics efficiently.

This instructor-led, live training (online or onsite) is aimed at beginner-level to advanced-level data professionals who wish to learn how to query, manage, optimize, and administer data within Teradata environments through theory and hands-on practice.

By the end of this training, participants will be able to:

• Understand the distributed architecture and parallel execution model of Teradata.
• Write optimized SQL queries from basic selection to advanced analytics.
• Design and execute large-scale data loading and transformation processes.
• Diagnose and improve query performance using tools like EXPLAIN and statistics.
• Manage permissions, resources, and shared environment best practices.

Format of the Course

• Interactive presentations and conceptual explanations.
• Practical exercises based on real-world scenarios.
• Integration and optimization labs using official tools like Teradata Studio or BTEQ.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Introduction to Teradata

Module 1: Teradata Fundamentals and Architecture

• What is Teradata and what is it used for?
• Parallel architecture: AMPs, PEs, BYNET
• Data distribution and hashing
• Key concepts: sessions, spool, locks
• System connection: Teradata Studio / BTEQ / SQL Assistant

Module 2: Introduction to SQL in Teradata

• Basic SELECT, WHERE, ORDER BY
• Data types and casting
• Math and date functions
• Using ALIAS, CASE expressions
• Teradata-specific operators (TOP, QUALIFY, SAMPLE)
• Guided practice: queries on real tables

Module 3: Joins, Subqueries, and Set Operators

• INNER, LEFT, RIGHT, FULL OUTER JOIN
• Joins without ON clause (cartesian product)
• Scalar and correlated subqueries
• UNION, INTERSECT, MINUS
• Practical exercises on data integration

Module 4: Analytical and OLAP Functions

• RANK(), ROW_NUMBER(), DENSE_RANK()
• Data partitioning with PARTITION BY
• Windowing with OVER() and ORDER BY
• LAG(), LEAD(), FIRST_VALUE()
• Use cases: KPIs, trends, cumulative values

Module 5: Data and Table Management

• Table types: permanent, volatile, global temporary
• Creating and using secondary and join indexes
• Insert, update, and delete operations
• MERGE, UPSERT, and duplicate control
• Transactions and lock control

Module 6: Optimization and Performance Tuning

• Teradata Optimizer: how it chooses execution plans
• Using EXPLAIN and COLLECT STATISTICS
• Skew and how to avoid it
• Query design best practices
• Bottleneck identification (spool, locks, redistribution)
• Practice: comparing optimized vs. non-optimized queries

Module 7: Data Partitioning and Compression

• Partition types: Range, Case, Multi-Level
• Benefits and practical use in large queries
• Block Level Compression (BLC) and Columnar Compression
• Advantages and limitations

Module 8: Data Loading and Extraction

• TPT (Teradata Parallel Transporter) vs. FastLoad / MultiLoad
• Bulk loading vs. batch inserts
• Error handling and retries
• Exporting results to files or external systems
• Basic automation with scripts and utilities

Module 9: Basic Administration for Technical Users

• Roles and permissions
• Resource control (Query Bands, Priority Scheduler)
• Monitoring with DBQLOGTBL, DBC.Tables, ResUsage
• Best practices for shared environments

Module 10: Final Integration Lab

• End-to-end practical case:
• Data loading
• Transformation and aggregation
• Building KPIs with OLAP functions
• Optimization and EXPLAIN
• Final export
• Discussion of best practices and common mistakes

Summary and Next Steps