Programa do Curso

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

Requisitos

  • 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
 35 Horas

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