InfoSphere Information Analyzer (IA) provides capabilities to profile and analyze data to deliver trusted information to any organization.
Data quality specialists use InfoSphere Information Analyzer to scan samples and full volumes of data to determine their quality and structure. This analysis helps to discover the inputs to the data integration project, ranging from individual fields to high-level data entities. Information analysis enables any organization to correct problems with structure or validity before they affect the data integration project.
After data is analyzed, data quality specialists create data quality rules to assess and monitor heterogeneous data sources for trends, patterns, and exception conditions. These rules help to uncover data quality issues and help the organization to align data quality metrics throughout the project lifecycle. Business analysts can use these metrics to create quality reports that track and monitor the quality of data over time. Business analysts can then use IBM InfoSphere Data Quality Console to track and browse exceptions that are generated by InfoSphere Information Analyzer.
Understanding where data originates, which data stores it lands in, and how the data changes over time is important to develop data lineage, which is a foundation of data governance. InfoSphere Information Analyzer shares lineage information with the rest of Information Server by storing it in the metadata repository. Other Information Server components can access lineage information directly to simplify the collection and management of metadata across any organization.
Here is a sample IA report showing the number of Constant, Unique and Null values in the entire input data on chosen columns with some additional information. This is one of the several reports that IA can generate.