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Cognos DecisionStream
For Data Warehouse Developers

Duración: 5 días.

Metodología: presencial.

Dirigido a

  • Modelador / Administrador COGNOS.
  • This course is intended for developers who are planning a data warehouse or have a data warehousing background.
  • It is designed for the more experienced systems professional involved in the provision of MIS solutions. Typically, this audience includes BI project consultants, project analysts, project leaders, and database administrators.

Pre-requisitos

Participants should have:

  • Knowledge of Windows.
  • Database concepts.
  • Dimensional analysis concepts and working knowledge of SQL.

Objetivo

Is a five-day, instructor-led course designed for enterprise data mart builders. It will teach users how to move, merge, consolidate, and transform data from a range of data sources to build and maintain subject-area data marts.

Decision Stream data mart targets include all the major relational databases and are typically designed to create best practices dimensional data mart solutions (star schema).

Specifically, the course deals with the dimensional framework, builds, and templates. The dimensional framework is a repository for reference structures (dimensions, hierarchies, lookups, and dimension templates) that promotes the reuse of the structures. Builds are uinits of work that progress through data acquisition, transformation, and delivery. Templates are objects that define source and target attributes for dimension data.

Temario

  1. Introduction
  2. Create a catalog
  3. Create hierarchies
  4. Create basic builds
  5. Derivations
  6. Conformed dimensions
  7. Create hierarchies and lookups manually
  8. History preservation
  9. Processing dimensional history
  10. Additional lookup techniques
  11. Data delivery in depth
  12. Processing late arriving facts
  13. Facts in depth and merging
  14. Aggregation and partitioning
  15. Jobstreams
  16. The command line interface
  17. User-defined function s and variables
  18. Ragged hierarchies
  19. Pivoting
  20. Resolving data quality issues
  21. Troubleshooting and tuning
  22. Packing and navigator
 
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