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About the Data Warehouse Application Console

The Data Warehouse Application Console (DAC) provides a framework for the entire life cycle of data warehouse implementations. It allows you to create, configure, and execute modular data warehouse applications in a parallel, high-performing environment. For information about the DAC process life cycle, see About the DAC Process Life Cycle.

The DAC complements the Informatica ETL platform. It provides application-specific capabilities that are not pre-built into ETL platforms. For example, ETL platforms are not aware of the semantics of the subject areas being populated in the data warehouse nor the method in which they are populated. The DAC provides these application capabilities at a layer of abstraction above the ETL execution platform, as illustrated in Figure 3.

Figure 3.  DAC Application-Specific Capabilities

Important DAC Features

Important DAC features allow you to do the following:

Minimize install, setup, and configuration time

• Create physical data model in the data warehouse
• Accelerate Informatica configuration
• Set language, currency, and other settings
• Develop data warehouse applications

Manage metadata driven dependencies and relationships

• Generate custom ETL execution plans
• Automate change capture for the Siebel transactional database
• Capture deleted records
• Assist in index management
• Perform metadata validation checks
• Perform dry-run development and testing
• Provide in-context documentation

Provide reporting and monitoring to isolate bottlenecks

• Perform error monitoring and email alerting
• Perform structured ETL analysis and reporting

Utilize performance execution techniques

• Automate full and refresh mode optimization rules
• Set the level of Informatica session concurrency
• Load balance across multiple Informatica servers
• Restart from point of failure
• Queue execution tasks for performance (See Figure 4.)

  The DAC manages the task execution queue based on metadata driven priorities and scores computed at runtime. This combination allows for flexible and optimized execution.

  Figure 4.  Task Execution Queue