Data Analysis

Data Analysis analyzes and filters information in complex XML documents. You can use this analysis to create a library, that contains Data Analysis tools to quickly and easily transform your data in IBM® App Connect Enterprise.

XML files are flexible, but can be long and complex. You might be interested in a small subset of data. However, it can be difficult to construct a model to filter and analyze this subset of data using traditional methods. Existing business intelligence (BI) tools work best with well-structured relational data.

In a Data Analysis project, you analyze a set of sample XML documents according to the content of the data. This content is defined in a Data Analysis profile that you specify when you create the project. When you analyze your sample XML documents, new data and new data structures within them are retained in the Data Analysis model. Repeated data and data structures are not added. After this analysis is complete, you can explore your Data Analysis model, which is a summary of your sample data, select relevant elements in the Data Analysis model, and then add them to a target model. Use the target model to produce a library that contains your Data Analysis tools, which you can use at run time to transform incoming data. The Data Analysis tools that are created include a map, schema file, validation stylesheet and subflow.

An overview of the process is shown in the following figure: The figure shows the process, as described earlier in the text.

The key steps are as follows:
  1. Create a Data Analysis project. See Creating a Data Analysis project.
  2. Analyze sample XML documents. See Analyzing sample XML documents.
  3. Create a target model. See Creating a target model.
  4. Populate and edit your target model. See Populating a target model from your sample XML documents and Modifying a target model in the Target Model editor.
  5. View and edit your target model in database format. See Editing the database representation of the target model in the Target Model editor and Data Analysis database setup.
  6. Create a library that contains Data Analysis tools. See Creating Data Analysis tools.
  7. Use the Data Analysis tools to work with your data in the Integration Development perspective.