Översikt
| Kurskod | KM201SE | Leveranstyp | Classroom
(Hands-on labs) |
|---|---|---|---|
| Kurslängd | 4.0 dagar | Kurstyp | |
| Listpris | Set by Partner |
This course works with Information Server V8.7
In this course, you will learn about the features of IBM InfoSphere DataStage V8 and learn how to build and run DataStage Extract, Transform and Load (ETL) jobs. Also covered will be information on DataStage V8.1 in its IBM Information Server environment. You will learn how to build DataStage parallel jobs that read and write data to and from a variety of data stores including sequential files, data sets, and relational tables. Additionally, you will learn how to build parallel jobs that process data in a variety of ways: business transformations, data filtering, data combining, data generation, sorting, and aggregating.
This course replaces course IBM InfoSphere DataStage Essentials V8 (KM200SE). This is the Classroom version of Instructor-led Online course IBM InfoSphere DataStage Essentials V8.7 (ILO) (3M201SE), Self-Paced Virtual Course DataStage Essentials - SPVC (2I444SE), and Web-based course DataStage Essentials - Web Based (1I444SE).
Målgrupp
This is a basic course for project administrators and ETL developers responsible for data extraction and transformation using DataStage.
Förkunskaper
You should have:
- Knowledge of the Windows OS
- Familiarity with Open Database Connectivity (ODBC) and relational database access technique
Mål
- Combine data using lookup, join, and merge stages
- Create jobs that read from and write to sequential files
- Make jobs that read from and write to a relational database using the connector stages
- Build jobs that process data using transformations, combinations, filterings, sortings and aggregations
- Conduct searches and impact analyses
- Produce job reports
- Construct DataStage users
- Administer the DataStage environment
Nyckelområden
- Deployment
- Administration console
- Designer
- Director
- Administrator
- Accessing sequential data
- Retrieve relational data using connectors
- Combining data
- Transforming data
- Repository
- Job control
- Metadata
- Parallel framework
- Complex Flat File stage
- Slowly Changing Dimensions
- MQ Connector
- Performance Analyzer and Resource Estimator utilities