Information Analyser

IBM® InfoSphere® Information Analyser is a part of Information Server and helps users to understand data quickly through data quality assessment, flexible data rules design and analysis, and quality monitoring capabilities.

What Does It Do?

  • Information Analyser helps users to derive more information from enterprise data by exposing more information about the data which can then be used to increase the quality of data-centric projects.
  • It integrates with IBM InfoSphere QualityStage and provides direct re-use of data rule definitions reducing development effort.
  • It has deep profiling capabilities which provide a comprehensive understanding of data at the column, key, source, and cross domain levels and multi-level rules analysis (by rule, by record, by pattern) to provide the ability to evaluate, analyse, and address multiple data issues by record rather than in isolation.
  • It provides a scalable platform for interrogating massive volumes of data and supports Data Governance initiatives through auditing, tracking and monitoring of data quality conditions over time.
  • It has enhanced data classification capabilities to help focus attention on common personal identification information to build a foundation for Data Governance
  • It proactively identifies data quality issues, finds patterns and sets up baselines for implementing quality monitoring efforts and tracking data quality improvements.

Why Is That Useful?

  • A complete Source System Profiling and Analysis capability enables users to easily understand and classify data, display data using various semantics such as format, classification, or value in order to allow rapid identification of data anomalies, validate column/table relationships and drill down to exception rows for further analysis.
  • Data Rules can be created an edited in IBM InfoSphere DataStage, IBM InfoSphere QualityStage, or Information Analyzer and shared among all three applications utilising the same familiar interface, so that users can align data quality metrics throughout the project lifecycle.
  • Time to value of data integration projects is reduced by leveraging the Information Server architecture since analysts can easily initiate processing for one process while continuing to analyse other data, and then deliver the resulting information to others.
  • Data projects contain trusted information and lower the risk of propagating bad data since data quality issues and anomalies are uncovered early in a data integration project, building a foundation for Data Governance.
  • The Rules Analysis capability adds another dimension to data profiling by creating and executing common data rules to perform trending, pattern analysis and establish baselines consistently across heterogeneous data sources
  • User Annotations support comprehensive descriptive information enabling users to add their own business names, descriptions, business terms and other attributes to tables, columns, or rules.
  • Common Metadata across all IBM InfoSphere Information Server product modules enables the sharing of profiling results/information with other data integration processes. For example, a DataStage designer would immediately be able to see that a column has been profiled and anything noted by the profiler.