Overview of the BIRT design creation process
Complete the following steps to create a BIRT design:
*Selecting a template and a data source
*Selecting, inserting, and limiting displayed data
*Formatting the BIRT design
*Saving and viewing the BIRT design
Selecting a template and a data source
The template you choose determines the basic layout of your design and which elements are available in the BIRT design. Report items include a report title, page numbers, report‑creation date, and a table in which to display report data. You can select which items appear in a BIRT design. Report Studio provides a set of templates you can choose from. For example, to create a simple listing design, select standard template, or to create a cross tab design, select cross tab template. Templates are organized in categories, and can also contain themes that determine the basic appearance of the BIRT design. The theme controls the appearance of the report table.
Data sources contain data sets which contain the data fields that are displayed in the BIRT design. BIRT iHub provides sample data sources of each type for use in Report Studio. A BIRT design accesses data from the following types of data
sources:
*A template containing a data set
*An information object data source
*A BIRT data object data source
Selecting, inserting, and limiting displayed data
After you choose a data source, the Table Builder wizard in Report Studio appears, enabling you to select and arrange the data fields to use in the BIRT design. As you select data fields in Table Builder, Report Studio displays the data columns in the order in which you select them. Rearrange the data fields in Table Builder so that the columns appear in the logical order you expect.
When data sources contain more data than you need to display in your BIRT design, you can limit the data retrieved using filters. Table Builder enables you to create a data set filter that narrows the scope of data retrieved from the data source and displayed in the BIRT design. Data set filters can significantly improve design‑time performance if the data set contains a large amount of data.