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Course Content
1. Parallel Architecture
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Architecture for data stages MPP and SMP systems Customers using Datastage and their use Techniques for data collecting and splitting Simultaneous execution Overview of several datastage positions.
2. DataStage Configuration and Administration
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Assemble and set up a project Configuration file and related files Adding Users and distributing roles.
3. Metadata
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Create a schema. Importing metadata techniques. Column propagation in real time. Functionalities of a repository. Schema Documents.
4. Handling data from Files
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Transferring data to and from a framework Chronological file The use of CFF (Complex Flat File) Use of datasets and file sets Describe the remote data usage of the FTP stage Identify XML data exporting and importing.
5. Databases
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Database-specific stage attributes and stage selection Decide on a source database Choose a target database Dealing with sources and targets for NLS databases.
6. Data Transformation
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Conversions of explicit and implicit types, Mappings of output Transformer stage choices in comparison to previous phases Capabilities of a transformer stage (including: DataStage macros, restrictions, system variables, link ordering, stage variables, link variables, and link variables.) Determine the procedure to add features that the current DataStage levels do not offer. (For instance, buildups, user-defined functions, and wrappers).
7. Job Components
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Copy, edit, filter, or switch between Stages SORT phase Remove duplicates and funnel Steps of join, lookup, and merge Stage of an aggregate Change apply/change capture SCD stage, surrogate key generator stage Switch Stage, Stage row and column generators Steps of column export and import Testing phases.
8. Job Design
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Specify parameters Communal containers Several instances of work Coordinating datasets Simple and parallel procedures Job-specific pre- and post-routines Display understanding of batch vs real-time task design.
9. Monitoring and Troubleshooting
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Similar job evaluation Identify potential areas for performance improvement. Common mistakes and their fixes Job postings.
10. Job Management and Deployment
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Understanding of advanced discoveries Comparison of jobs and impact assessments Process for change control Code import and export.
11. Job Control and Runtime Management
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Establishing a work hierarchy Phases, triggers, and displays of activity Resetting aptitude Scheduling work Message processors DS job is a command-line tool Job Locks and File Status Information.
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