IBM WebSphere Information Analyzer evaluates the content and structure of your data for consistency and quality. WebSphere Information Analyzer also helps you to improve the accuracy of your data by making inferences and identifying anomalies.
Understanding the actual quality, content, and structure of your data is an important first step when you need to make critical business decisions. The quality of your data depends on many factors. For example, correct data types, consistent formatting, retrievability, and usability are just a few of the criteria that define data of good quality. If the structure and content of your data is poor, the information that you need is difficult to access. As a consequence, the design, development, or testing activities that use the data can be significantly impaired.
WebSphere Information Analyzer helps you to assess the quality of your data by identifying inconsistencies, redundancies, and anomalies in your data at the column, table, and cross-table level. WebSphere Information Analyzer also makes inferences about the best choices regarding data structure. Inferences help you to learn more about the optimal structure of your data and what you can do to improve the quality of your data.
To create a data profiling project in WebSphere Information Analyzer, you must follow a few steps. First, an administrator configures data source connections, creates a project, adds metadata to the project, and then configures security options for the project. After the project is configured, you can run analysis tasks. After an analysis completes, you can review the results and inferences and then make decisions based on the evaluation. You can choose to have your review and inference decisions delivered to other authorized users within the user interface. For example, you can create a report that displays a summary of analysis results or you can share your results with other suite components. The results are saved in the metadata repository and are available to all authorized suite users.
