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Continuously Manage and Monitor Data Quality IBM® InfoSphere™ Information Analyzer helps quickly & easily understand data by offering data quality assessment, flexible data rules design & analysis, and quality monitoring capabilities. These insights help derive more information from enterprise data to accelerate information-centric projects.

  • • Deep profiling capabilities - provide a comprehensive understanding of data at the column, key, source, and cross domain levels
  • • Multi-level rules analysis (by rule, by record, by pattern) unique to the data quality space - provides the ability to evaluate, analyze, and address multiple data issues by record rather than in isolation
  • • Shared metadata foundation - integrate the modules across IBM InfoSphere Information Server and IBM InfoSphere Information Server for System z in support of the enterprise
  • • Native parallel execution for enterprise scalability - enables high performance against massive volumes of data.
  • • Supports Data Governance initiatives through auditing, tracking and monitoring of data quality conditions over time
  • • Enhanced data classification capabilities help focus attention on common personal identification information to build a foundation for Data Governance
  • • Proactively identify data quality issues, find patterns and set up baselines for implementing quality monitoring efforts and tracking data quality improvements
  • Languages supported: English, Chinese (simplified and traditional), Japanese, Korean, Spanish, Portuguese (Brazil), Italian, German, and French.

Features and benefits

IBM InfoSphere Information Analyzer provides these unique capabilities:

  • Complete Source System Profiling and Analysis via a revolutionary user interface enables users to easily understand and classify data, display data using various semantics such as format, classification, or value in order to allow the customer to quickly identify data anomalies, validate column/table relationships and drill down to exception rows for further analysis. Data quality assessment functions include column, primary key, foreign key, cross-domain and baseline analysis.
  • Improve time to value of data integration projects leveraging the Information Server architecture, analysts can easily initiate processing for one process while continuing to analyze other data, and then deliver the resulting information to others. Core profiling utilizes the strength of the underlying parallel engine to stream data and process multiple requests without requiring technical expertise.
  • Ensure data projects contain trusted information and lower the risk of propagating bad data Needs around business metadata tend to differ from one enterprise to the next. For this reason, there is no "one size fits all" meta-model. In addition to being able to customize the entry page to the application, administrators can extend the application with custom attributes on both business categories and business terms.
  • Comprehensive, Easy-to-use Reports Offering approximately 80 configurable reports for the visualization of analysis/trends/metrics to assist uncovering data quality concerns and help understand results quickly and efficiently.
  • Rules Analysis 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
  • Scheduling analysis activities Information Analyzer utilizes the Information Server scheduling service, allowing both adhoc and scheduled execution of profiling, rules, and metrics, as well as scheduling via external CLI calls (e.g. by DataStage, Tivoli, script, etc.)
  • 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.
  • Direct Integration with InfoSphere Business Glossary and InfoSphere Metadata Workbench
  • Common Metadata across all IBM InfoSphere Information Server and IBM InfoSphere Information Server for System z product modules enables the sharing of profiling results/information with other data integration processes. For example, a IBM InfoSphere DataStage designer would immediately be able to see that a column has been profiled and anything noted by the profiler (ie. column ABC needs to be cleansed before the ETL process).
  • The Security Framework : in IBM InfoSphere Information Analyzer utilizes project-, role- and user-based approaches to control and limit access to sensitive analytical information including the ability to restrict drilldown to original data sources.
  • Scalabilitythrough native parallel execution enables high performance profiling against massive volumes of data; also leverage Virtual Tables and Columns to analyze and monitor data strata or segments without requiring changes to a customer’s host database.
  • REST API and CLI expose data quality assessment and monitoring results for downstream utilization such as custom dashboards or integration with other applications.
  • Flexibilitythrough IBM InfoSphere Information Analyzer for Linux on System z to perform these functions directly on the mainframe so that you can: - Leverage existing mainframe resources to maximize the value of your IT investments - Take advantage of the scalability, security, manageability and reliability of the mainframe - Add mainframe information integration work load without added z/OS operational costs