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.
Share Data Rules – Data Rules can be created an edited in IBM InfoSphere DataStage, IBM InfoSphere QualityStage, or Information Analyzer and shared among all 3 applications utilizing the same familiar interface. This allows you to align data quality metrics throughout the project lifecycle.
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 - Uncover data quality issues and anomalies early in a data integration project and improve success rates with extended classification to build a foundation for Data Governance.
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 (i.e. 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 (i.e. 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.
Scalability through 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.
Flexibility through 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
Learn what’s new in v8.7