© 2013 IBM Corporation Information Management Discovering the Value of IBM InfoSphere Information Analyzer IBM Software Group 1Discovering the Value of IBM InfoSphere Information Server Steven Green

© 2013 IBM Corporation Information Management InfoSphere Information Analyzer  Identify data quality issues early to reduce project risks  Monitor quality metrics over time for compliance  Create business confidence with trusted information  Results promotable across IBM Information Server  Perform data quality assessment  Define business rules to monitor data quality  Establish stewards for governance of data quality Requirements Benefits Assess data quality and facilitate ongoing data quality monitoring and exception management

© 2013 IBM Corporation Information Management Common Data Problems

© 2013 IBM Corporation Information Management Pain – The Cost of Dirty Data Inaccurate or incomplete data is a leading cause of failure in business-intelligence and CRM projects 83% of data integration projects either overrun or fail Low data quality costs companies $611 billion annually Undetected defects will cost 10 to 100 times as much to fix upstream 25% of time is spent clarifying bad data Lack of consumer confidence Lost opportunities Scrap and rework Increased costs

© 2013 IBM Corporation Information Management Business Drivers For Information Quality  Poor data quality costs U.S. businesses over $600 billion each year  Data deteriorates up to 3% every month  What is the key to integrating corporate data? Having the right data before you start Ensuring adequate data quality Understanding source data Creating complex transformations Creating complex mappings Ensuring adequate performance Collecting and maintaining meta data Finding skilled programmers Providing access to meta data Ensuring adequate scalability Integrating 3rd party tools Ensuring adequate reliability

© 2013 IBM Corporation Information Management InfoSphere Information Server – Profiling and Quality Features Column Analysis Key Analysis Cross Domain Analysis Quality Monitoring Quality Rule Validation

© 2013 IBM Corporation Information Management Column Analysis Understanding Source Data 1. Assess data content 2. Assess data Structure 3. Quality within and across heterogenous systems InfoSphere Information Server – Profiling and Quality Features

© 2013 IBM Corporation Information Management Column Analysis  Domain values and validation  Data classification  Data properties  Formats 8Discovering the Value of IBM InfoSphere Information Server

© 2013 IBM Corporation Information Management InfoSphere Information Server – Profiling and Quality Features

© 2013 IBM Corporation Information Management Gain Insight into your data Column Analysis InfoSphere Information Server – Profiling and Quality Features

© 2013 IBM Corporation Information Management Key Analysis Column Analysis Validation of keys 1. Primary/Foreign Key 2. Data Preview 3. Data Relationships InfoSphere Information Server – Profiling and Quality Features

© 2013 IBM Corporation Information Management  Automated Primary-foreign key discovery  Full statistics on discovered keys  Data preview  Missed records, orphan foreign keys Primary Foreign Key Discovery 12Discovering the Value of IBM InfoSphere Information Server

© 2013 IBM Corporation Information Management InfoSphere Information Server – Profiling and Quality Features

© 2013 IBM Corporation Information Management Gain Insight into your data Improve Time to Value Key Analysis Column Analysis InfoSphere Information Server – Profiling and Quality Features

© 2013 IBM Corporation Information Management InfoSphere Information Analyzer – Profiling Features Column Analysis Key Analysis Cross Domain Analysis Assess Data Integrity 1. Redundant Information 2. Referential Integrity 3. Unknown business rules

© 2013 IBM Corporation Information Management  Cross-domain relationships  Data redundancy  Data preview  Missed records, orphan foreign keys Cross Domain Analysis 16Discovering the Value of IBM InfoSphere Information Server

© 2013 IBM Corporation Information Management InfoSphere Information Server – Profiling and Quality Features

© 2013 IBM Corporation Information Management Column Analysis Key Analysis Cross Domain Analysis Increase Productivity Gain Insight into your data Improve Time to Value InfoSphere Information Server – Profiling and Quality Features

© 2013 IBM Corporation Information Management Column Analysis Key Analysis Cross Domain Analysis Quality Rule Validation InfoSphere Information Server – Profiling and Quality Features Uncover Data Issues 1. Missing Values 2. Inconsistencies 3. Type alignment

© 2013 IBM Corporation Information Management Rule Based Analysis 20Discovering the Value of IBM InfoSphere Information Server  Rules Analysis: Enables ongoing measurement and baseline reporting of information quality –Validation of data rules individually or within a broader set –Establishment of benchmark thresholds

© 2013 IBM Corporation Information Management Over 130 Data Rules Available for Everyone!  Predefined rule definitions available out-of-the-box to reduce effort –Populated for all projects when Information Analyzer is installed –~200 rules cover a broad array of common data validation conditions Common domains: keys, national identifiers, dates, country codes, addresses, etc. Basic conditions: completeness checks, valid values, range checks, aggregated totals, equations, etc. –Serve as models, templates, and examples for additional rule design –Copy within a project and make changes to establish your own models Increased Productivity and rule examples – out of the box!

© 2013 IBM Corporation Information Management InfoSphere Information Server – Profiling and Quality Features

© 2013 IBM Corporation Information Management Column Analysis Key Analysis Cross Domain Analysis Quality Rule Validation Ensure Trusted Information Increase Productivity Gain Insight into your data Improve Time to Value InfoSphere Information Server – Profiling and Quality Features

© 2013 IBM Corporation Information Management Column Analysis Key Analysis Cross Domain Analysis Quality Monitoring Quality Rule Validation InfoSphere Information Server – Profiling and Quality Features Monitor Over Time 1. Baseline Reporting 2. Validation of Rules 3. Benchmark Thresholds

© 2013 IBM Corporation Information Management 25Discovering the Value of IBM InfoSphere Information Server Continuously Manage and Monitor Data Quality Identify and mitigate risk. Where do we need to implement more stringent controls? How do we ensure that critical data meets our standards? Establish baselines of information View differences between different executions including baseline Analyze trends

© 2013 IBM Corporation Information Management InfoSphere Information Server – Profiling and Quality Features

© 2013 IBM Corporation Information Management Ensure Trusted Information Gain Insight into your data Improve Time to Value Increase Productivity Eliminate Risk Key Analysis Cross Domain Analysis Quality Monitoring Quality Rule Validation Column Analysis InfoSphere Information Server – Profiling and Quality Features

© 2013 IBM Corporation Information Management “Just having an ETL engine is not enough,” says Janes. “With Information Analyzer, we can see what the data actually looks like, quickly adjust project requirements and refine development code early in a project’s lifecycle.” – Kevin Janes, Senior Solutions Architect, Shared Health “We now can deliver services that previously only larger companies could handle,” says Janes. “IBM Information Server is an integral part of our ability to be who we are.” – Kevin Janes, Senior Solutions Architect, Shared Health InfoSphere Information Analyzer's data analysis capabilites are multi-faceted to suit any organization's data analysis and profiling needs. The addition of Rules analysis is a key aspect for organizations looking to be able to track data quality over time. Our clients tell us that trusted information based on solid data quality is critical for them to take sound business decisions in order to be successful and Information Analyzer helps customers do just that. - Timothy Moon, Managing Director – Zenith Solutions InfoSphere Information Server – Profiling and Quality Features

© 2013 IBM Corporation Information Management 29Discovering the Value of IBM InfoSphere Information Server SIMPLIFIED CHINESE HINDI JAPANESE ARABIC RUSSIAN TRADITIONAL CHINESE TAMILTHAI FRENCH GERMAN ITALIAN SPANISH BRAZILIAN PORTUGUESE

© 2013 IBM Corporation Information Management IBM InfoSphere Information Analyzer Value Improve time to value of data integration projects Eliminate the risk of proliferating bad data Ensure data sources contain trusted information Monitor data sources to “always” contain trusted information Benefits Gain insight into your data sources Reduce the time to assess and analyze data by 50+% Improve personnel productivity Maintain data quality consistency throughout data lifecycle