Slide 1What is master data management?Why MDM?MDM Problem StatementKey Elements of MDM Solutions - IKey Elements of MDM Solutions - 2The lifecycle of dataData Discovery Tools show what/how much is out thereSemantic Technologies and Policy Engines automate complex tasksKey Elements of MDM Solutions - 3Key Elements of MDM Solutions - 4Focusing on differentiation through industry data modelsDifferentiating from the CompetitionWhere to learn moreIn the next lecture …Questions?News PRESENTATIONMaster DataManagementInstructor: Pankaj MehraTeaching Assistant: Raghav GautamLec. 4April 8, 2010ISM 158What is master data management?•Processes and technologies for creating the go to source of consistent, integrated information about core business entities•Master DataAbout:-Customers- Products- Parts- Employees- SuppliersWhat:-Entities- global ID- Attributes- TaxonomyStandard global schemaCentralized governanceWhy 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 reportingMDM 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 modelKey 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 interestKey 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 sourcesThe lifecycle of dataData Discovery Tools show what/how much is out thereSemantic Technologies and Policy Engines automate complex tasksdiscoverapply policyclassifyStorageResourceManagementApplicationResourceManagementBusinessProcessResourceManagementFeatureExtractionCategoryMetadataSemanticMetadata(meaning)SpecialplatformCaptureat sourceMigrate toplatformIntegrateon demandManagein placeKey Elements of MDM Solutions - 3•Entity Taxonomies–Describe how entity names, attribute names, attribute values are to be interpreted•Ontologies can define more complex semanticsSource: Wand, Inc. catalogKey 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 martsFocusing on differentiationthrough 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 Core80% universal data model80% universal data modelTechRetailFSIGovt/DefenseComm/mediaMDIEnergy…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 DataJul 6, 2008 ... Martin Arlitt, Keith Farkas, Subu Iyer, Preethi Kumaresan, Sandro Rafaeli. HP Laboratories. HPL-2008-83. http://www.hpl.hp.com/techreports/2008/HPL-2008-83.pdfWhere 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_Management (chase the See Also links)•Learn about industry-standard data models–ADRM.net, IBM xyz Industry Frameworks–Learn about ACORD and insurance industryIn the next lecture …•Guest lecture by Dr. Julie WardQuestions?•NEWS
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