The DAC provides a framework for the entire life cycle of data warehouse implementations. It allows
you to create, configure, execute, and monitor 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” on page 17.
The DAC complements the Informatica ETL platform. It provides application-specific capabilities that
are not prebuilt 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.
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
- ■ Set language, currency, and other settings
- ■ Design subject areas and build execution plans
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 dry runs and test runs of execution plans
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 incremental mode optimization rules
- ■ Set the level of Informatica session concurrency
- ■ Load balance across multiple Informatica servers
- ■ Restart from point of failure
About DAC Repository Objects
All DAC repository objects are associated with a source system container. For more information about source system containers, see “About Source System Containers” on page 15 and “About Object Ownership in the DAC” on page 38.
The DAC repository stores application objects in a hierarchical framework that defines a data warehouse application. The DAC allows you to view the repository application objects based on the source system container you specify. The source system container holds the metadata that corresponds to the source system with which you are working.
A data warehouse application comprises the following repository objects:
■ Subject area. A logical grouping of tables related to a particular subject or application context, as well as the tasks that are associated with the tables. Subject areas are assigned to execution plans, which can be scheduled for full or incremental loads. A subject area also includes the tasks required to load the subject area tables.
■ Tables. Physical database tables defined in the database schema. Can be transactional database tables or data warehouse tables. Table types can be fact, dimension, hierarchy, aggregate, and so on, as well as flat files that can be sources or targets.
■ Task. A unit of work for loading one or more tables. A task comprises the following: source and target tables, phase, execution type, truncate properties, and commands for full or incremental loads. When you assemble a subject area, the DAC automatically assigns tasks to it. Tasks that are automatically assigned to the subject area by the DAC are indicated by the Autogenerated flag in the Tasks child tab of the Subject Areas tab.
■ Task Groups. A group of tasks that you define because you want to impose a specific order of execution. A task group is considered to be a “special task.”
■ Execution plan. A data transformation plan defined on subject areas that needs to be transformed at certain frequencies of time. An execution plan is defined based on business requirements for when the data warehouse needs to be loaded. An execution plan comprises the following: ordered tasks, indices, tags, parameters, source system folders, and phases.
■ Schedule. A schedule specifies when and how often an execution plan runs. An execution plan can be scheduled for different frequencies or recurrences by defining multiple schedules.
About the DAC Process Life Cycle
The DAC is used by different user groups to design, execute, monitor, and diagnose execution plans. These phases together make up the DAC process life cycle, as shown in Figure 5. The phases of the process and the actions associated with them are as follows:■ Setup
- ■ Set up database connections
- ■ Set up ETL processes (Informatica)
- ■ Set up email recipients
■ Design
- ■ Define application objects
- ■ Design execution plans
■ Execute
- ■ Define scheduling parameters to run execution plans
- ■ Access runtime controls to restart or stop currently running schedules
■ Monitor
- ■ Monitor runtime execution of data warehouse applications
- ■ Monitor users, DAC repository, and application maintenance jobs
