Ibm Websphere Qualitystage Methodologies, Standardization, And Matching

IBM WebSphere QualityStage provides data cleansing capabilities to help ensure quality and consistency by standardizing, validating, matching, and merging information to create comprehensive and authoritative information for multiple uses.

IBM Information Server is a revolutionary software platform that helps organizations derive more value from the complex heterogeneous information that is spread across their systems.

It enables organizations to integrate disparate data and deliver trusted information wherever and whenever needed, in line and in context, to specific people, applications, and processes.

This IBM Redbooks publication documents the procedures for implementing IBM WebSphere QualityStage and related technologies using a typical merger and acquisition financial services business scenario. The scenario covers all dimensions of data cleansing, standardization, and matching rules, job design and deployment through a data integration life cycle.

The book offers a step-by-step approach to implementing IBM WebSphere QualityStage on Red Hat Enterprise Linux 4.0 platform accessing information that is stored on IBM z/OS and IBM AIX platforms. If you are an IT architect, Information Management specialist, or Information Integration specialist who is responsible for developing IBM WebSphere QualityStage on a Red Hat Enterprise Linux 4.0 platform, you will find the information in this book helpful.

About the Authors
Nagraj Alur is a a Project Leader with the IBM ITSO, San Jose Center. He holds a master's degree in computer science from the Indian Institute of Technology (IIT), Mumbai, India. He has more than 33 years of experience in database management systems (DBMSs) and has been a programmer, systems analyst, project leader, independent consultant, and researcher. His areas of expertise include DBMSs, data warehousing, distributed systems management, database performance, information integration, and client/server and Internet computing. He has written extensively on these subjects and has taught classes and presented at conferences all around the world. Before joining the ITSO in November 2001, he was on a two-year assignment from the Software Group to the IBM Almaden Research Center, where he worked on Data Links solutions and an eSourcing prototype.

Alok Kumar Jha is currently working as a BI Solution Architect in Industry Solutions at the IBM India Software Lab (ISL) in Bangalore. His expertise includes designing and developing BI Solutions across the verticals. He earned his MBA degree from FMS-IIRM, Jaipur, and masters in Statistics from Hindu College, Delhi University. He earned his bachelors in Statistics from Kirori Mal College, Delhi University. He has eight years of experience in Data Warehousing/BI. He has worked with IBM for the past four years. Prior to joining the ISL at IBM he worked at Cognizant Technology Solutions, iGate Global Solutions, and SPSS in various roles. Alok's core area of expertise includes end-to-end Data Warehousing/BI. His skills include Dimensional Modeling, Data Integration (ETL, EII), Relational Database Reporting, Multidimensional Modeling and Analysis (OLAP), Data Mining, and Statistical Analysis. Alok has designed ETL processes that involved application data such as SAP R/3 for designing and developing Profitability Analysis (CO-PA) for multidimensional analysis for different KPIs. He has worked extensively on different BI platforms, including DB2 Framework for Business Intelligence, Cognos Framework for Business Intelligence, Microsoft Framework for Business Intelligence, SPSS, and SAS technologies.

Barry Rosen is currently serving as Director of Best Practices and Data Management in the Center of Excellence for Data Integration and a "champion" of Data Profiling, Data Quality, and Metadata at IBM. His past roles include Director of Enterprise Architecture/Data Warehousing, Technical Architect, and Principal Consultant. He holds a master's degree in Engineering Management and Computer Information Systems from Northeastern University. Barry has designed, managed, and implemented multiple highly available, large scale transaction, data warehousing/mining and business intelligence solutions in various vertical market segments worldwide including financial, telecom, insurance, pharmaceutical and retail sectors. He has over 25 years of technical architecture and customer focused information management expertise. He has provided technical leadership for business system architecture and applications including ERP, CRM, and data warehousing. Barry has consulted on various complex, high-risk, time sensitive systems for companies such as Epsilon Data Management, Fidelity Investments, Wellington Management Company, Investors Bank and Trust, and Harte-Hanks Data Technologies.