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IBM Information Server. Understand - Information Analyzer. IBM Information Server Delivering information you can trust. Support for Service-Oriented Architectures. Transform. Deliver. Understand. Cleanse. Discover, model, and govern information structure and content. Standardize, merge,

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ibm information server

IBM Information Server

Understand - Information Analyzer

ibm information server delivering information you can trust
IBM Information ServerDelivering information you can trust

Support for Service-Oriented Architectures





Discover, model, and govern information structure and content

Standardize, merge,

and correct information

Combine and restructure information for new uses

Synchronize, virtualize and move information for in-line delivery

Platform Services







the ibm solution ibm information server delivering information you can trust
The IBM Solution: IBM Information ServerDelivering information you can trust

IBM Information Server

Unified Deployment





Information Analyzer

Data profiling for understanding what data you have and how it relates to other data, plus data analysis for measuring and monitoring ongoing data quality.

Unified Metadata Management

Parallel Processing

Rich Connectivity to Applications, Data, and Content

data profiling
Critical Problems:

You don’t know what data is really in your legacy systems

Sources have changed or are new and unknown


Data values and relationships are inconsistent and divergent from documented rules

Incomplete and missing documentation

Data sources are never static and frequently change without warning

Alternative Approach

Labor intensive, resource devouring process

Never review 100% of data elements

No infrastructure to support maintenance

No standardized approach across projects

1st generation tools document but don’t address the problem resolution

Data Sources

ERP from acquisition

Mainframe manufacturing system

Parts BOM

External Lists




Billing / Accounts

Data Profiling
about information analyzer
Automates your data discovery process

Enables you to understand your data before starting development

Eliminates the risk and uncertainty of using bad data

Useful in any type of data migration project

Analyzes every data attribute and reverse engineers the true meta data of your source

Reduces time to analyze data

Data Sources

ERP from acquisition

Mainframe manufacturing system

Parts BOM

External Lists




Billing / Accounts

About Information Analyzer
ibm information analyzer
IBM Information Analyzer
  • Reduce Time to Value of Data Projects
  • Increase the Productivity of Data Personnel
  • Assess Data Quality & Consistency across the Enterprise
  • Results sharable across IBM Information Server

Data Profiling: the process of analyzing a data sources to determine its content, quality and structure

what does information analyzer provide
What does Information Analyzer provide?
  • Source System Analysis
    • Provides the key understanding of the source data
      • Column & Domain analysis
      • Table/Primary Key analysis
      • Foreign Key analysis
      • Cross-Domain analysis
  • Iterative Analysis
    • Leverages the analysis to facilitate iterative tests
      • Baseline analysis


Key Analysis



Source 2

Source 1

Foreign Key &

Cross-Domain Analysis

source system analysis
Source System Analysis
  • Column & Domain analysis
    • Infers from content a column’s classification, physical properties, and frequency distribution
  • Table/Primary Key analysis
    • Validates the uniqueness of the identified key column, which allows us to ensure that a given row of data can be clearly identified and related to other data
  • Cross-Domain & Foreign Key analysis
    • Syncronizes the structure, relationships and integrity of data environments by finding and validating otherwise unknown relationships and identifying critical integrity violations that need to be rectified.
column analysis chart view
Column Analysis: Chart View
  • Frequency Distribution
    • View Frequency Distribution either in Tabular or in Graph
    • Add user defined value to Frequency Distribution
    • Generate Reference Tables
    • Sort and Filter Frequency Data
column analysis properties
Column Analysis: Properties
  • Properties
    • Six property values are inferred for each column: Data Type, Length, Precision, Scale, Nullability and Cardinality Type.
    • Distribution of data types, lengths, precisions and scales is displayed graphical.
primary key analysis results
Primary Key Analysis Results
  • Reviewing Duplicates
    • View Summary of Distinct and Duplicated Values
    • Display list of all Primary Key values and #/% Duplicated.
baseline analysis
Baseline Analysis
  • Baseline Differences
    • Detailed results for the column level.
    • Results include the column level summaries of distinctions for both Structure (Defined and Inferred) and Content.
roi food distribution
ROI: Food Distribution.
  • Company Facts :
  • Largest distributor in North America
  • Four major acquisitions in last two years
  • 12,000 branded products
  • 30,000 clients
  • 11 operating centers

Project Goals



Integration of supply chain management systems

Profit margin analysis systems

Field expansion, and take along project

Staff changes and limited documentation related to acquired systems

Only 7% of data being analyzed, but bad data causing 20% of cost overruns

Estimate 10k hours and $650kin costs to support first four projects

80% productivity gain for analyzing data sources

$504,000 annual savings in lower development and maintenance costs

Repeatable process for all future projects that ensures good, actionable data

roi top us life insurance company
ROI: Top US Life Insurance Company

Company Facts :

  • #1 Largest Life Insurance Company in USA
  • 138US$ billion in assets under management
  • Offer complete like of life insurance, investment, retirement and related products

Project Goals



Competitive pressures requires the company to further enhance an existing competitive advantage – 360 degree customer view and 24\7 data availability.


Better customer visibility.

Reduced costs by eliminating expensive and time-consuming investigations of detailed data.

Redeploying an investigator saves $130k annually.

Detailed customer data resided in ten disparate legacy systems with little to no documentation.

Presenting raw detailed data 24\7 was impossible.

Leveraging IBM allows for consistent data formats, validate data domains, define business rules linking policy data.