Understanding Data Views

In Liquid Data a stored query and a target schema comprise a data view.

Figure 6-1 Components of a Data View

 

To create a data view from a query:

• You first create a query and save it.
• Then you configure a data view data source description for the query in the WebLogic Server Administration Console.

To create a virtual data source in this way, you must first create a query and save it to the Liquid Data server repository, then configure a data view data source description for the query in the WebLogic Administration Console. It is recommended that you create the query and save it to the repository using the Data View Builder, but it is also possible to use hard-coded queries in generally the same way.

The following sections explain what a data view is and how to use a data view data source with the assumption that you are using the Data View builder to construct the query. Also included is a clarification of the relationship between a query and a a data view.

Functionally, a data view extends the power of a stored query through its association with a target schema that describes the data. This combination allows a data view to be identified in the Data View Builder as a data source for additional queries.

The following sections describe in detail how to create Liquid Data data views and use such views as data sources. Also included is a discussion of the relationship between a query and a data view.

A Data View Use Case

eWorld Co, a company that through multiple mergers and acquisitions has 50,000 employees, also has multiple payroll systems. Using Liquid Data, information in each of these systems can be accessed. The company also has two relational databases from separate vendors for tracking incentive bonuses. Human Resources very frequently gets questions about when such bonus payments will show up in affected employee's paychecks.

• To enable HR to get answers to employees quickly and economically, an Information Technology data architect creates a query using Liquid Data that can access relevant information from the multiple payroll systems and the company's incentive bonus databases.
• Once satisfied that the query works, the IT architect creates a data view and makes it available to an HR data specialist. This specialist can then use Liquid Data to quickly get answers to inquiries from individual employees about their bonus payments.

The benefits of this approach are significant:

• A single integrated view can be created for use throughout an enterprise. Access to sensitive information is controlled and consistency is maintained.
• HR can quickly get the information it needs without having to either staff up with its own data architect or get in the queue for expensive and low-availability IT custom programming services.
• Since data views are typically created by information architects, more time can be spent designing and testing the generalized query.

Simple and Parameterized Data Views

The difference between a simple and a parameterized data view is that a parameterized data view has one or more input parameters. Specifically views that centrally contain functional sources such as an application view, web service, custom function, or stored procedure often require an input parameter.

Using Data Views as Data Sources

From the Data View Builder, you access a data view as you would any other data source. There is no limit to the number of data views that can be used in creating a new query, although currently there may be performance implications to nesting data views. A data view can reference on another data view.