Uploaded byEduardo Castro
Introduccion a SQL Server Master Data Services
Dr. Eduardo Castro discusses the importance of Master Data Management (MDM) in improving organizational efficiency and effectiveness through better data integration and governance. He highlights the challenges faced by businesses with multiple systems and incorrect data, emphasizing the need for centralized management processes and tools to maintain authoritative views of master data. The document also covers how Microsoft's MDM can enable Business Intelligence (BI) by providing a scalable and secure framework for data management and analysis.
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Introduccion a SQL Server Master Data Services
- 1. Dr. Eduardo Castro,MBA ecastro@grupoasesor.net http://ComunidadWindows.org
- 2. Investment Strategy Improve Empower Your Enable IT Organizational People Efficiency Effectiveness Self-Service Collaborative Trusted, access & across your scalable & insight value chain secure Familiar IT Alignment, interface & Management Accountability tools you own & & Ownership today Interoperability Low Total Cost of Ownership Leverage your existing Infrastructure
- 3. Investment Strategy Improve Empower Your Enable IT Organizational People Efficiency Effectiveness Self-Service Collaborative Trusted, access & across your scalable & insight value chain secure Familiar IT Alignment, interface & Management Accountability tools you own & & Ownership today Interoperability Low Total Cost of Ownership Leverage your existing Infrastructure
- 4. Investment Strategy Improve Empower Your Enable IT Organizational People Efficiency Effectiveness Self-Service Collaborative Trusted, access & across your scalable & insight value chain secure Familiar IT Alignment, interface & Management Accountability tools you own & & Ownership today Interoperability Low Total Cost of Ownership Leverage your existing Infrastructure
- 5. Session Objective(s): What is MDM? Discuss Analytical MDM drivers Understand BI/MDM process & data flow Value proposition for MDM How Microsoft MDM enables BI MDM integration with SQL, IS, AS
- 8. Analytic •My sales reports are wrong •Analysts can’t maintain dimensions •Marketing can’t analyze by patch area ERP - USA Data Warehouse or Analytic App Operational •Europe keeps changing the color •New products never include the French product name •I can’t pick the right Boeing •Difficulty coordinating multiple systems – Operational MDM •Difficulty managing dimensions – Analytic MDM ERP - Europe •Or both – Enterprise MDM 8
- 10. MD – Slowlychanging reference data shared across systems MDM – An application for creating and maintaining an authoritative view of master data including policies and procedures for access, update, modification, viewing between systems across the enterprise PEOPLE THINGS PLACES ABSTRACT • Customers • Products • Stores • Contracts • Vendors • Organizational • Wells • Warrantees • Sales people units • Power lines • Time • Employees • Recipes • Geographical • Metrics • Parts areas • Partners • Storage bins • Patients • Documents
- 12. Is this areal problem? Tiger Brands has 23 different business units, each using a different customer tracking system Microsoft had 9 “Boeing” top parent records with 5907 different “Boeing” companies not linked to any top parent records. Compass Bank reduced the cost center maintenance effort from 30 person days a month to 2 by implementing a central management process and system
- 13. Where is thereal Boeing? Boeing Boeing Boeing Inc Aut_Boeing Boein’ (Renton) HR Doc Purchasing Asset Mgmt DB
- 14. Boeing MDM Merge/Match Role Security Master Data Stewardship Versioning Hierarchy Mgmt Workflow Approval Boeing Boeing Boeing Inc Aut_Boeing Boein’ (Renton) HR Doc Purchasing Asset Mgmt DB
- 15. Operational Analytic •Any domain hub •Stewardship portal •Attribute association •Hierarchy Management •Async Notifications •Business rules •App-specific dimension builds •App-specific integration •Workflow •Versioning •Federation •Email Notifications •Granular security Bulk •Model metadata oriented - •Data quality tools SSIS Message •Transaction logging oriented - BTS •Deployment tools •Packaged content Office Integration Control “homeless” SAP Integration data 15
- 16. Customer Product •Any domain hub •Stewardship portal Specific Consistent •Attribute association Matching Schema •Business rules Algorithms •Workflow •Email Notifications Industry •Granular security standards External •Data quality tools Services •Transaction logging •Deployment tools Complex data •Packaged content model •Model metadata Federation Diverse Scenarios High data volume 16
- 17. New Features •3 TierUI •Admin UI •LOBI •Metadata •Model Deployment •Powershell •Services API Improvements Completed Product Adjustments •Accessibility SQL •Setup & Install •DB Schema Perf. •Infragistics Imp. •Configuration Manager •UI Updates •Internationalization •Business Rules •Multi-Tenancy •Authentication •Security Config •Model Deployment •Setup •World Readiness •SharePoint Int. Office •Services API •UI Renovation •Security •ULS for MDM Features & •Documentation •Windows Auth Improvements •MetaData Explorer •Workflow Stratature Features •Performance •Entity & Hierarchy Management •Schema, Business Rule, •Version Management Granular Security, Testing •Transaction History/Compliance •Stress & Long Haul •Role-based, Granular Security •LOBi •Multi/any-Domain Models Stratature Base •Async Export * •Central system of record •Matching * •Business Rules •Notifications •Bulk SQL Interfaces 17
- 18. Master Data •Ubiquitous •Decays 5 to 15% Master Data •Reconciliation required Fact Data •Relatively Static 85 – 95% Fact or Transaction •Single Source Data
- 19. Master Data isAlive Needs Constant Management to Remain Valid Decay Corruption Conflict Data decays as the world changes Data is corrupted as people and M&A and external relationships around it processes touch it • Deaths • Web Forms • Inter- and Intra-company • Mergers • Mobile Forms • External Mandates (Wal- • Marriages • Call Center Mart / RFID) • Divorce • Data Maintenance • Multi-source Systems • Bankruptcy • Data Input • Federation • Births • Internal Processing • Cross geography issues • Legislation (reporting, rules) • Data Silos Problems multiply with scale and complexity • Number of geographies / governments • Number of entities / customers / products • Number of applications
- 20. Good BI =Good Facts + Good Dimensions Dimensions define the structure for analysis Products Customers Centers – Revenue and Cost Chart of Accounts Fiscal Period Hierarchies support consolidation and drill- down along dimensions Good facts + bad dimensions = Bad BI
- 21. International and domesticaccounting standards and legislation are demanding more visibility, transparency and audit ability of systems Can you track changes in dimensions? Do you know who made the changes? Do you know when changes occurred? Can you produce a dimension from Q2 last year? Most analytics tools use a single administrator Few if any have version control
- 22. Customers often believethey can have a single homogenous DW or ERP that provides all data with all dimensional categories needed for analysis. Frank conversations usually reveal that this is not realistic
- 23. The most importantMaster Data is often “homeless” How do you map multiple customer IDs into one recognized relationship? Your ERP has a product group but how do you reflect other important product attributes and hierarchies? How do you exclude the effect of acquisitions? How do you merge multiple chart of accounts into a common structure? How can you analyze customers by market?
- 24. Data Stewardship Support Data Browsing and Editing Change Management • Application Integration • Hierarchy Management • Versioning • User transparency • Entity Management • Histories • Approval and Notification • Role based and Context sensitive • Slowly Changing Dimensions • Manual Data Conflict Resolution browsing • Slowly Changing Hierarchies and Reconciliation • Ubiquitous integration • Data Steward Console • Arbitrarily defined views Data Rules Engine Security Master Data • Customizable • Context Sensitive Entity Views Synchronization • Pre-configurable • Value and Role Based Security • Write-back • Extensible • Security based on Metadata and • Real time updates • Integrated with workflow attributes • Automatic Data Conflict • Factors in authoritativeness • Transaction logging and rollback Resolution and Reconciliation • Bulk Import/Export into hub Master Data Metadata High Speed Merge/Match Enterprise integration • Entity tagging Engine • Thin client capable • Entity prioritization • Ad-hoc real-time lookups • Office thick client available • Lineage • Bulk capabilities • SharePoint integration • Impact Analysis • Third party data integration • Easier on-boarding • Referential Tracking • Diff/Update capable • Third party application • Descriptions, Usages, Custom • Cross mode results compatible integration • Federated aggregation
- 25. Process agnostic centralrepository for master data that is highly available to organization Allows us to build multiple dimensions from complete representation of the master data from department or organization Web based UI and security model enables users to have very limited update permissions without providing access to sensitive data. Server based data provides organization with access to master data 24/7
- 26. AS is greatat BI analytics Cross dimension analysis Slicing, dicing, aggregations Usually requires a cube context AS not good at managing change Core engine not optimized for edits Write-back possible, but difficult to audit, manage & surface No workflow, notifications, business rules, auditing, stewardship UI, fuzzy matching
- 27. MDS provides theability to manage hierarchies, using explicitly (arbitrary) relationships or derived from data Provide attributes and attribute groups at parent and child nodes Slowly changing dimension semantics Allows for the automatic and accurate creation of hierarchy paths based on attribute relationships Enforces the structure and security of the hierarchy by preventing inaccurate relationship assignments This provides business intelligence users with a wide array of possible dimensions
- 28. Benefits Managemultiple versions without cluttering individual BI application ie AS, PPS , TM1, Cognos Planning Version flag Support effective dates Analysis Services Permit multiple snapshots of dimensions Used for VSCD (very slowly changing dims) Customer2007, Customer 2008, Customer
- 29. Benefits Weprovide robust business rule engine and workflow to maintain data quality for dimensions. Transaction Management & Auditing Analysis Services Clean up the data presented to the business Flag problems in records Automatically categorize entities
- 30. SQL Server AnalysisServices SQL Server Integration Services Excel & SQL Server Reporting Services Planning Applications LOBI/BDC Integration
- 31. Traditional BI AS & SSIS loads warehouse Source SSIS DW MDS AS loaded from WH MDS from WH Dimensions Mastered BI SSIS loads MDS WH Dimensions loaded from MDS AS loaded from WH Source SSIS MDS WH AS
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- 33. Central management ofdimensions Product, Cost Center, Chart of Accounts, Customer, others…. Audit-ability / Trace-ability Tracking of changes by user, time and other change details Version control Preservation of past dimension versions and comparison highlights among versions Promotion of new versions to subscribing systems and notification of version changes to users Integration with OLAP, ERP and data warehouse
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- 35. Ing. Eduardo Castro,PhD ecastro@grupoasesor.net