IBM InfoSphere DataStage Essentials (v11.5)
This course enables the project administrators and ETL developers to acquire the skills necessary to develop parallel jobs in DataStage. The emphasis is on developers. Only administrative functions that are relevant to DataStage developers are fully discussed. Students will learn to create parallel jobs that access sequential and relational data and combine and transform the data using functions and other job components.
Learning Journeys or Training Paths that reference this course:
Data Integration Architect
Data Integration Developer
Information Analysis – Data Integration Architect
Information Server – Developer Role
Objetivos
Describe the Information Server architecture and how DataStage fits within it
Describe the Information Server and DataStage deployment options
Use the Information Server Web Console and the DataStage Administrator client to create DataStage users and to configure the DataStage environment
Import and export DataStage objects to a file
Import table definitions for sequential files and relational tables
Design, compile, run, and monitor DataStage parallel jobs
Design jobs that read and write to sequential files
Describe the DataStage parallel processing architecture
Design jobs that combine data using joins and lookups
Design jobs that sort and aggregate data
Implement complex business logic using the DataStage Transformer stage
Debug DataStage jobs using the DataStage PX Debugger
Administración y programación bases de datos
Disponible en formato e-learning
Disponible en formato presencial
Disponible en formato a distancia
Descargar la información del curso
Subvención disponible
A través de Fundae, cumpliendo requisitos.
Duración
20 horas
- Dificultad 50%
- Nivel alcanzado 80%
Dirigido a
Project administrators and ETL developers responsible for data extraction and transformation using DataStage.
Conocimientos requeridos
Basic knowledge of Windows operating system
Familiarity with database access techniques
Temario
1. Introduction to DataStage
2. Deployment
3. DataStage Administration
4. Work with Metadata
5. Create Parallel Jobs
6. Access Sequential Data
7. Partitioning and Collecting Algorithms
8. Combine Data
9. Group Processing Stages
10. Transformer Stage
11. Repository Functions
12. Work with Relational Data
13. Control Jobs
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