1. Master Data Management Instructor: Pankaj Mehra Teaching Assistant: Raghav Gautam Lec. 4 April 8, 2010 ISM 158

2. What is master data management? Processes and technologies for creating the go to source of consistent, integrated information about core business entities Master Data About: -Customers - Products - Parts - Employees - Suppliers What: -Entities - global ID - Attributes - Taxonomy Standard global schema Centralized governance

3. Why MDM? Supporting single view of … business imperatives Gain visibility and control over vital information –Cleanse, standardize, consolidate –Apply data governance Examples –MDI Improve procurement and distribution by removing duplications, errors and inconsistencies in supply chain data –HLS Track physician outreach sales activities for compliance reporting

4. MDM Problem Statement The goal: Create and maintain a high-quality view for the whole enterprise, across all its functions, of mission-critical information objects Starting with: duplicate, inconsistent or incomplete records in locally governed silos, each with its own quality control and data model

5. Key Elements of MDM Solutions - I Business Logic –Complex rules capturing the strategic analytics and data quality intent of the business –Complex rules capturing regulatory intent Example –A defense signals agency in Australia records as many cell phone calls as can –Rules define the entities of interest

6. Key Elements of MDM Solutions - 2 Data integration tools –Data discovery –Extraction, Transformation & Loading (ETL) –Data lifecycle management A market campaign management project needs to optimize the allocation of advertising dollars –Composite Discovery Server could help you locate the right source for “PC sales data by geography” –Informatica PowerCenter 9 or Composite Integration Server will let you set up complex information extraction and transformation steps using a visual query language –Database archiving tools from IBM/Princeton Softech will let you sample and manage the retention of data from diverse sources

7. The lifecycle of data

8. Data Discovery Tools show what/how much is out there

9. Semantic Technologies and Policy Engines automate complex tasks discover apply policy classify Storage Resource Management Application Resource Management Business Process Resource Management Feature Extraction Category Metadata Semantic Metadata (meaning) Special platform Capture at source Migrate to platform Integrate on demand Manage in place

10. Key Elements of MDM Solutions - 3 Entity Taxonomies –Describe how entity names, attribute names, attribute values are to be interpreted Ontologies can define more complex semantics Source: Wand, Inc. catalog

11. Key Elements of MDM Solutions - 4 Common Data Model –capturing core entities in a standard schema –Allows long-term enterprise-wide investment in quality and analytics regimens The HP Enterprise Data Warehouse consolidates customer, product, and sales data from thousands of operational systems and in turn consolidates hundreds of data marts

12. Focusing on differentiation through industry data models ADRM and other providers are helping standardize the schema of common data types across and within industries Equally potent open- source initiatives are part of the Semantic Web and Linked Object Data work –E.g. Dublin Core 80% universal data model Tech Retail FSI Govt/ Defense Comm/ media MDI Energy …

13. Differentiating from the Competition Ultimately, data quality improvement is achieved through going the extra mile using every trick in the book What helps? –Statistics –Semantics Example: –Statistical analysis of whether data missing from resource utilization traces of supply chain management applications is MAR (missing at random) or NMAR (not missing at random) A Systematic Approach for Improving the Quality of IT Data Jul 6, 2008... Martin Arlitt, Keith Farkas, Subu Iyer, Preethi Kumaresan, Sandro Rafaeli. HP Laboratories. HPL-2008-83. http://www.hpl.hp.com/techreports/2008/HP L-2008-83.pdf

14. Where to learn more Whitepapers from suppliers of MDM technology: –Informatica/Siperian –IBM/Initiate Industry analysts: Gartner, in particular Wikipedia: http://en.wikipedia.org/wiki/Master_Data_Manag ement (chase the See Also links) http://en.wikipedia.org/wiki/Master_Data_Manag ement Learn about industry-standard data models –ADRM.net, IBM xyz Industry Frameworks –Learn about ACORD and insurance industry

15. In the next lecture … Guest lecture by Dr. Julie Ward

16. Questions?

17. NEWS PRESENTATION