Enterprise Business Intelligence Solutions

Transcription

1 EWSolutions Enterprise Business Intelligence Solutions Presented to DAMA Wisconsin April 12, 2007 by John Faulkenberry EWSolutions 2004 Enterprise Warehousing Solutions, Inc. (EWSolutions) 1

2 EWSolutions EWSolutions is a Chicago-headquartered strategic partner and full life-cycle systems integrator providing both award winning strategic consulting and full-service implementation services. This combination affords our clients a full range of services for any size enterprise architecture, managed meta data environment, and/or data warehouse/business intelligence initiative. Our notable client projects have been featured in the Chicago Tribune, Federal Computer Weekly, Crain s Chicago Business, won the 2004 Intelligent Enterprise s RealWare award and DM Review s 2005 World Class Solutions award. Our client list includes: Arizona Supreme Court Bank of Montreal Becton, Dickinson and Company Blue Cross Blue Shield Branch Banking & Trust (BB&T) British Petroleum (BP) California DMV College Board Corning Cable Systems Defense Logistics Agency (DLA) Delta Dental Driehaus Capital Management Eli Lilly and Company Federal Bureau of Investigation (FBI) Fidelity Information Services Ford Motor Company GlaxoSmithKline Harris Bank Harvard Pilgrim HealthCare HCSC (BC/BS) HP (Hewlett-Packard) Information Resources Inc. Janus Mutual Funds KeyBank Loyola Medical Center Manulife Financial Mayo Clinic Microsoft National City Bank Nationwide Neighborhood Health Plan NORC Pillsbury SAIC Schneider National Secretary of Defense/Logistics SunTrust Bank Target Corporation The Regence Group Thomson Consumer Electronics (RCA) US Air Force US Navy US Transportation Command USAA Wells Fargo Best Business Intelligence Application Information Integration Client: Department of Defense World Class Solutions Award Data Management For more information on our Consulting Services or World-Class Training, call toll free 866.EWS.1100, ( ), the main number , or us at Info@EWSolutions.com 2007 Enterprise Warehousing Solutions, Inc. page 2

3 EWSolutions Background Founded in August 1997 and headquartered in Chicago Strategic consulting and full service systems integration Focused on Data Warehousing/Business Intelligence (DW/BI), Managed Meta Data Environments (MMEs), and Enterprise Information Management (EIM) Data Governance Information Architecture Data Stewardship Information Quality Management Reference & Master Data Management Data Warehousing & Business Intelligence Meta Data Management Structured Data Management Unstructured Data Management EIM Services Information Security Management Reference & Master Data Transaction Data Business Intelligence Data Unstructured & Semi-Structured Data 2007 Enterprise Warehousing Solutions, Inc. page 3

4 EWSolutions Clients Driehaus Capital Management USTRANSCOMM 2007 Enterprise Warehousing Solutions, Inc. page 4

5 Agenda Business Intelligence Concepts DW/BI Architecture Business Intelligence Applications BI Design Concepts DW Design Concepts BI Management Enterprise Business Intelligence Approaches Break Critical Success Enablers -- Oh yeah, we need that too! Information Architecture Information Quality Management Reference & Master Data Management Information Security Management Meta Data Management Data Stewardship & Governance Enterprise Information Management Roles & Organizations Client Experiences Keys to Success EIM Roadmap 2007 Enterprise Warehousing Solutions, Inc. page 5

6 Definitions - 1 Data: raw facts, stored out of context and without semantic meaning. Information: data in context meaning, format, timeframe, relevance Data Warehouse (DW): An integrated, centralized, historical, relational database and the related software used to collect, cleanse, transform and load data from a variety of operational sources for reporting and analysis by business professionals. Data Mart: A database of aggregated and summarized historical data typically focused on a specialized subject area for reporting and analysis by business professionals. A data mart may be may be independent, or part of a larger data warehousing environment and fed from a data warehouse (dependent) Enterprise Warehousing Solutions, Inc. page 6

7 Definitions - 2 Business Intelligence (BI): Knowledge workers (executives, managers, staff) using information to answer the questions that inform business decisions (formerly known as decision support). Business Intelligence Environment: The information, support, tools and technology that enables knowledge workers to find the answers they need. Business Intelligence Management: Providing the information, technologies & support knowledge workers need to find the answers that inform business decisions. BI Big Picture vs. BI Information Delivery? 2007 Enterprise Warehousing Solutions, Inc. page 7

8 DW/BI Architecture Source Systems Staging Area Data Warehouse Business Intelligence Environment Information Data Mart 2007 Enterprise Warehousing Solutions, Inc. page 8

9 Business Intelligence Applications - 1 Ad Hoc Query & Reporting Enterprise Reporting OLAP Online Analytical Processing Desktop Cubes MOLAP ROLAP Statistical Analysis Data Mining (pattern identification, predictive analysis) What If Modeling & Forecasting Analytical Applications (e.g., budgeting, sales force analysis) Dashboards and Scorecards Business Performance Management Executive Information Systems 2007 Enterprise Warehousing Solutions, Inc. page 9

10 DW/BI Design Concepts Data Warehouse (Traditional) Subject Oriented the data is stored in business subjects (e.g., patient, provider, location, episode) Integrated data from disparate sources transformed and stored together in a consistent format Non Volatile the data is not updated by the users Time Variant provides historical perspective vs. operational systems Data Warehouse 2007 Enterprise Warehousing Solutions, Inc. page 10

11 DW/BI Design Concepts Dimensional Data Marts Fact Tables & Dimension Tables Star Schemas & Variations Shared Dimensions Data Mart Org Geo Time 9,624 6,553 Prod Chan??? 2007 Enterprise Warehousing Solutions, Inc. page 11

12 DW/BI Design Concepts Dimensional Data Warehouse Data Warehouse Enterprise Data Warehouse Dependent Data Marts Data Warehouse Data Marts 2007 Enterprise Warehousing Solutions, Inc. page 12

13 DW/BI Architecture Source Systems Staging Area Data Warehouse Data Marts Business Intelligence Environment Information Data Warehouse Ad Hoc Query & Reporting Enterprise Reporting Multi- Dimensional Analysis Data Mart Statistical Analysis Data Mining What-If Modeling Analytics Dashboards & Scorecards 2007 Enterprise Warehousing Solutions, Inc. page 13

14 DW/BI Enabling Technology & Processes Data Modeling Extract, Transform, and Load (ETL) Data Profiling Data Cleansing Metadata Management 2007 Enterprise Warehousing Solutions, Inc. page 14

15 Managing the BI Environment User Interfaces BI Portals Information Directories (business meta data) Data Security Data Views, User Groups, Permissions Education / Training Problem Management Help Desk, Level 2, Level 3 Complex Query & Reporting Assistance The BI SWAT Team Usage & Performance Monitoring 2007 Enterprise Warehousing Solutions, Inc. page 15

16 Other Business Intelligence Activities Define the DW/BI Strategy and Architecture Implement Data Warehouses and Data Marts Implement Business Intelligence Technology Implement BI Analytic Applications Provide Reports Communicate / Promote Business Intelligence 2007 Enterprise Warehousing Solutions, Inc. page 16

17 Agenda Business Intelligence Concepts DW/BI Architecture Business Intelligence Applications BI Design Concepts DW Design Concepts BI Management Enterprise Business Intelligence Approaches Break Critical Success Enablers -- Oh yeah, we need that too! Information Architecture Information Quality Management Reference & Master Data Management Information Security Management Meta Data Management Data Stewardship & Governance Enterprise Information Management Roles & Organizations Client Experiences Keys to Success EIM Roadmap 2007 Enterprise Warehousing Solutions, Inc. page 17

18 Enterprise BI Approaches Integrated Enterprise Master Plan vs. Independent Data Marts Operational Applications Islands of Data Reporting Systems TOPPS ES-9000 HPE-980 RX42 VAX Cluster AMRS-Advanced Medical RIS- Record Radiology System Information System LAB/LIS- Laboratory Information System VAX(Burlington) IPS- Inter Practice System PSIMED HPE-980 North E/B AS/400 MGD Claims Query AS/400 Pharmacare (outside vendor) Pharmaview (outside vendor) HP-992 NEDClinical Computer NED E/B ACPS- Automatic Claims Processing PASS - Patient System Appointment Scheduling ENCOUNTER System FFS - Fee For Service REF - Referrals Pharmacy DB Provider Master HP (9 series) MARS AMISYS Hospital Summary Quality Assurance Request Network & Medical Request Actuarial End User Request Claims Prov DB Drug DB Bulletin Board System (BBS) Pentium PC Healthchex AST 486 server MHUM - Mental Health Utilization MS SQL Management Server ASAP - Actuarial System Analysis Program ES-9000 GL GMIS-Claim Check SAS, SAS screens, DB2 Viewpoint and SAS dataset Decision Analyzer Actuarial SAS dataset HP937 NED Datawarehouse HSA dept. Lan Server NED Multiview GL and AP PHC Multi-view GL. PHC JV Finance Server PHC Network Development Server MAMSYS/PAPSYS (14) Foxpro Applications PHC Medical Services Server PHC Actuarial Analysis Server Dec Alpha Quantum Analytic Database PHC Pharmacy Server Medical Groups Financial Analysis Standard Adhoc Pharmacy Standard Adhoc Claims Standard Adhoc Health & Medical Standard Services (CQM, HSA) Adhoc Utilization Standard Adhoc Actuarial & Underwriting Standard Analysis Adhoc Sales & Mktg / Standard Network Development Adhoc Membership/Enrollment & Standard Billing Adhoc Legend HCD MGD NED PHC Multiple colors indicate the system is used by multiple divisions Enterprise Warehousing Solutions, Inc. page 18

19 Enterprise BI Approaches Iterative Delivery vs. IWBITWC (If We Build It, They Will Come) Think Global, Act Local Demand Driven vs. Supply-Driven Business Drivers Sponsors, Users, Benefits, Scope, Timing & Timeframe, Funding 2007 Enterprise Warehousing Solutions, Inc. page 19

20 Agenda Business Intelligence Concepts DW/BI Architecture Business Intelligence Applications BI Design Concepts DW Design Concepts BI Management Enterprise Business Intelligence Approaches Break Critical Success Enablers -- Oh yeah, we need that too! Information Architecture Information Quality Management Reference & Master Data Management Information Security Management Meta Data Management Data Stewardship & Governance Enterprise Information Management Roles & Organizations Client Experiences Keys to Success EIM Roadmap 2007 Enterprise Warehousing Solutions, Inc. page 20

21 Agenda Business Intelligence Concepts DW/BI Architecture Business Intelligence Applications BI Design Concepts DW Design Concepts BI Management Enterprise Business Intelligence Approaches Break Critical Success Enablers -- Oh yeah, we need that too! Information Architecture Information Quality Management Reference & Master Data Management Information Security Management Meta Data Management Data Stewardship & Governance Enterprise Information Management Roles & Organizations Client Experiences Keys to Success EIM Roadmap 2007 Enterprise Warehousing Solutions, Inc. page 21

22 Information Architecture Defining, maintaining and leveraging the master blueprint for semantic and physical integration of enterprise information assets. Enterprise Data Model Shared Data Requirements in Business Terms Subject Areas, Business Entities, Essential Attributes Business Process Alignment Information Value Chain Analysis Roadmap for EBI Data Integration Guides Implementation Tailoring Choices for The Perfect Fit Related Data Architecture Data Warehousing / Business Intelligence Architecture OLTP Database Architecture Technology, Distribution, Integration 2007 Enterprise Warehousing Solutions, Inc. page 22

23 Information Architecture Activities Enterprise Information Architecture Planning Enterprise Data Modeling Information Value Chain Analysis Defining the Database Technical Architecture Defining the Data Integration / MDM Architecture Defining the Business Intelligence Architecture Defining the Metadata Architecture Managing Enterprise Taxonomies Project Data Modeling Analysis and Design Data Requirement Specification Logical Data Modeling / Business Metadata Specification Physical Data Modeling / Technical Metadata Specification Data Model Quality Management Defining Data Modeling Standards Reviewing Data Model Quality Managing Data Model Versioning and Integration 2007 Enterprise Warehousing Solutions, Inc. page 23

24 Enterprise Data Modeling Subject Area Model example showing subjects and simple relationships between subjects Inventory Customer Sales Order Product Purchase Order Supplier Accounts Receivable Accounts Payable Deceptively simple but difficult to identify subjects and agree upon terminology across multiple business units!! 2007 Enterprise Warehousing Solutions, Inc. page 24

25 Information Architecture Deliverables - 1 Enterprise information architecture, including: Enterprise data model Business metadata Information product specifications Information value chain analysis Enterprise information supply chains Database architecture Data integration architecture EDI, EAI, EII, MDM, DW/BI 2007 Enterprise Warehousing Solutions, Inc. page 25

26 Information Architecture Deliverables - 2 Data modeling and database design standards Subject area model Conceptual, logical and physical data models Data model and database design reviews Configuration management and version control for data models 2007 Enterprise Warehousing Solutions, Inc. page 26

27 Information Quality Management Ensuring the health / fitness of information for an intended use What if nobody trusts the data in the warehouse? Define Aspects of Quality What to Define? What to Measure? Validity Integrity Semantic, Structural, Referential, Domain Accuracy / Correctness Currency / Currentness Precision Consistency 2007 Enterprise Warehousing Solutions, Inc. page 27

28 Information Quality Management Activities Define Information Quality Metrics Define Quality Requirements & Business Rules Semantic, Structural, Referential & Domain Integrity Reconciliation, Transformation, Standardization, Match/Merge Profile / Analyze / Measure / Monitor Quality Set Quality Service Levels / Certify / Audit Quality Cleanse, Integrate, Transform & Match/Merge Data Reactive Cleanup Develop Operational Procedures Monitor Operational Procedures Identify, Escalate and Resolve Information Quality Issues Proactively Implement & Validate Quality Requirements Educate / Develop Information Quality Awareness 2007 Enterprise Warehousing Solutions, Inc. page 28

29 What Is Reference Data and Master Data? Reference & master data provides the context for business transactions. External Reference Data Units of Measure, Currencies, FX Rates, Geopolitical Data, Location Codes, Industry Classification Codes Internal Reference Data Chart of Account Values, Reporting Hierarchies, Branches, Status Values, Product Codes Enterprise Master Data Customers, Employees, Vendors, Products, Parts, Controlling reference & master data is key to improving data quality Enterprise Warehousing Solutions, Inc. page 29

30 What Is Reference & Master Data Management? Controlling the creation, capture, storage, synchronization and consistent usage of data about the enterprise s core business entities. Ensuring the quality and valid use of controlled data values. OLTP, ERP, Data Warehouse, Dimensions in Data Marts and OLAP Cubes Customer Data Integration (CDI), Code Management, Hierarchy Management Maintaining a Golden Version of the Truth Controlling Defined Values (external and internal) Assigned to Data Stewards -- Data Governance Approval for Changes Define Values, Labels, Meanings & Cross-References Maintain Hierarchies & Other Relationships Retire Codes Never Deleted Integrating Master Data from Multiple Valid Sources Consolidation From Multiple Systems of Record Cleansing and Match/Merging Based on Defined Business Rules Distributing / Providing Access to Golden Copies Thru Replication (Publish & Subscribe) or Real Time Access Ensuring Validity, Integrity, Accuracy, Currency & Consistency 2007 Enterprise Warehousing Solutions, Inc. page 30

31 Information Security Management Ensuring the privacy, confidentiality and appropriate access and use of information assets. Internal and External Security Regulations, Standards, Rules, Classifications Permissions/Rights/Privileges Users, Roles, Groups, Views Define, Implement, Monitor, Resolve, Audit Across Multiple Environments -- Production, Dev/Test 2007 Enterprise Warehousing Solutions, Inc. page 31

32 What Is Meta Data? Data about Data??? The contextual data that explains the definition, control, usage, and treatment of data content within a system and across the enterprise. Information (in software and other media) and knowledge (in people s brains), within and outside an organization about the business meaning, physical characteristics and quality of your company s data and related entities (terms, processes, technology) Enterprise Warehousing Solutions, Inc. page 32

33 Meta Data is the Key Meta Data is business semantics data requirement specifications data model content data quality specifications data quality measurements source lineage information ETL operational performance data BI user administration data BI usage information Meta Data guides DW/BI data integration. Meta data expresses the information architecture. Meta data describes current data inventories. Meta data describes source-target mappings and transformations. Meta data guides information quality improvement. Meta data enables data governance decision making Meta data guides how data stewards manage data assets Enterprise Warehousing Solutions, Inc. page 33

34 Meta Data Repository 2007 Enterprise Warehousing Solutions, Inc. page 34

35 Metadata Sourcing Layer Software Tools Documents/ Spreadsheets Messaging/Transactions (EAI, web services, XML, etc.) Metadata Extract Metadata Extract Metadata Extract Applications (CRM, ERP, data warehouses, etc.) Websites/ E-Commerce Metadata Extract Metadata Extract Third Parties (business partners, vendors, customers, government agencies) Metadata Extract Managed Metadata Environment M e t a d a t a I n t e g r a t i o n L a y e r Metadata Management Layer Metadata Repository End Users (business and technical) Data Warehouse/ Data Mart(s) Applications (CRM, ERP, etc.) Metadata Marts Metadata Delivery Layer Websites/E-Commerce Third Parties (vendors, customers, government agencies) Messaging/Transactions (EAI, web services, XML, etc.) Business Users End Users (business and technical) End Users (business and technical) Software Tools 2007 Enterprise Warehousing Solutions, Inc. page 35

36 Metadata Management Activities Define the Metadata Architecture Create Metadata (through other EIM functions) Capture Metadata From Sources Integrate (Consolidate and Reconcile) Metadata Develop and Implement Integration Processes Perform Integration Processes Manage the Metadata Repository Install and Support Technology Monitor Integration Processes Monitor Usage and Performance Manage Storage Support Usage Distribute and Deliver Metadata Access and Analyze Metadata 2007 Enterprise Warehousing Solutions, Inc. page 36

37 Data Governance & Stewardship Managing information assets is a shared responsibility between business data stewards (at multiple levels) and data professionals. Data stewards: Trustees of enterprise data assets, with assigned responsibility and accountability. Data professionals: Curators and custodians of enterprise data assets and related technology, providing information management services. Data Governance: the exercise of decision-making, authority and control (planning, monitoring and enforcement) over data strategy, policies, issues, architecture, standards, practices, and projects. Governance is shared decision making about the rules for how to manage information assets. Data Stewardship: specifically assigned, entrusted business responsibility and formal accountability for managing enterprise information assets Enterprise Warehousing Solutions, Inc. page 37

38 Data Governance Organizations Data Governance Council Executive Data Stewards <5% Strategic Data Stewardship Committee Coordinating Data Stewards Escalation Path < 20% 80-85% Conflicts Resolved at this level Tactical Data Stewardship Teams Business Data Stewards Operational by Subject Area, not by LOB 2007 Enterprise Warehousing Solutions, Inc. page 38

39 Data Governance Activities Recruit Data Stewards / Form Data Governance Organizations Manage / Facilitate Meetings Define the Information Strategy (Vision, Goals, Objectives, Roadmap) Define Policies for Information Management and Use Define / Review / Approve Data Standards Manage and Resolve Data Issues Review / Approve Data Architecture Components Sponsor / Oversee Information Management Projects & Services Monitor Policy Conformance & Regulatory Compliance Estimate the Value of Information Assets Communicate / Educate / Promote Information Management 2007 Enterprise Warehousing Solutions, Inc. page 39

40 Agenda Business Intelligence Concepts DW/BI Architecture Business Intelligence Applications BI Design Concepts DW Design Concepts BI Management Enterprise Business Intelligence Approaches Break Critical Success Enablers -- Oh yeah, we need that too! Information Architecture Information Quality Management Reference & Master Data Management Information Security Management Data Stewardship & Governance Meta Data Management Enterprise Information Management Roles & Organizations Client Experiences Keys to Success EIM Roadmap 2007 Enterprise Warehousing Solutions, Inc. page 40

41 EIM Functional Framework Data Governance Information Architecture Data Stewardship Information Quality Management Reference & Master Data Management Data Warehousing & Business Intelligence Meta Data Management Structured Data Management Unstructured Data Management EIM Services Information Security Management Reference & Master Data Transaction Data Business Intelligence Data Unstructured & Semi-Structured Data 2007 Enterprise Warehousing Solutions, Inc. page 41

42 What is EIM? Enterprise Information Management (EIM) is the business processes, disciplines and practices used to manage data and information as enterprise assets. plans, policies, programs and procedures that ensure high quality data is available, controlled and effectively used to meet the information needs of all stakeholders. getting the right information to the right people at the right time. EIM is not a single technology or component, but a coordinated framework of disciplines for managing data and information assets throughout the organization Enterprise Warehousing Solutions, Inc. page 42

43 What is EIM? Enterprise Information Management (EIM) may refer to a business function consisting of several lower level functions and activities. an on-going program consisting of several projects, strategies, policies, standards and procedural guidelines. an organization of data professionals within IT. the wider community of business data stewards and data professionals performing EIM functions Enterprise Warehousing Solutions, Inc. page 43

44 Information is an Enterprise Asset Organizations that do not understand the overwhelming importance of managing data and information as tangible assets in the new economy will not survive. Tom Peters 2007 Enterprise Warehousing Solutions, Inc. page 44

45 EIM Goals 1. To understand the information needs of the enterprise and all stakeholders. 2. To capture, store, protect and ensure the integrity of the information needed. 3. To prevent inappropriate use of data and information. 4. To continually improve the quality and availability of information. 5. To provide clear, accurate, timely and consistent data to support effective business processing and informed decision making, leveraging the use of information assets to their full value while controlling costs. ********************* To align the information management infrastructure with business requirements. To manage information consistently across the enterprise (policies, standards). To promote consistent understanding of the meaning and context of data. To promote a wider and deeper understanding of the value of information assets Enterprise Warehousing Solutions, Inc. page 45

46 EIM Guiding Principles Data and information are enterprise assets. As such, they should be managed to ensure quality and appropriate use and to maximize their business value. Management of these assets is a shared responsibility between business data stewards and IT professionals (technical data stewards). Business data stewards: Trustees of enterprise data assets, with assigned responsibility and accountability. IT professionals: Curators and custodians of enterprise data and related technology assets, providing EIM services Enterprise Warehousing Solutions, Inc. page 46

47 Your EIM Program No two EIM programs are the same each is unique. Adopt the EIM components and best practices that are most appropriate. Tailor best practices to your organization, recognizing your unique needs while keeping true to your business goals. The best approaches maintain a longterm enterprise focus while implementing incrementally and iteratively Enterprise Warehousing Solutions, Inc. page 47

48 EIM Roles Information Workers Data Producers Information Consumers Data Stewards Business Data Stewards Coordinating Data Stewards Executive Data Stewards Governance Groups Data Governance Council Data Stewardship Committee Data Stewardship Teams EIM Center of Excellence (data professionals) EIM Leader Enterprise Data Architect Data Architects & Modelers Data Quality Analysts Database Administrators Data Security Administrators Metadata Administrators Data Integration Architects Data Warehouse Architect BI Analysts / Administrators 2007 Enterprise Warehousing Solutions, Inc. page 48

49 EIM Organizations Reporting Structures Information Technology CIO Committees Data Governance Council Executive Data Stewards Chief Data Steward (chair) EIM Leader (facilitator) CIO (sponsor) Application Engineering Infrastructure & Operations Project Management Office Business Process Engineering EIM Center of Excellence EIM Director Data Architects Data Modelers Data Quality Analysts Meta Data Administrators Data Integration Architects DW/BI Administrators Database Administrators Data Security Administrators Data Stewardship Committee Coordinating Data Stewards Chief Data Steward (chair) EIM Leader (facilitator) Enterprise Data Architect (facilitator) Subject Area Data Stewardship Teams Coordinating Data Steward (chair) Data Architect (facilitator) Business Data Stewards 2007 Enterprise Warehousing Solutions, Inc. page 49

50 EIM Technologies Various technologies are used to implement and sustain an EIM strategy, including: database management systems data modeling technology metadata repository business intelligence and information delivery technology data integration technology extract-transform-load (ETL) enterprise application integration (EAI) enterprise information integration (EII) data cleansing & data profiling technology master data management (MDM) applications enterprise content management 2007 Enterprise Warehousing Solutions, Inc. page 50

51 Keys to EIM The keys to an effective EIM program include: Executive sponsorship Business participation Quantified business value Clear goals and SMART objectives Clearly defined processes and deliverables Clearly identified roles and responsibilities Staffing, organization and leadership Clearly assigned authority and empowerment Appropriate on-going funding Supporting technology Education & training Cultural change management 2007 Enterprise Warehousing Solutions, Inc. page 51

52 EIM Roadmap Assessment Where Are We Today? Deployment Make It So! Target Definition Where Do We Want To Be? Socialization Are We All On Board? Transition Planning How Do Get There? 2007 Enterprise Warehousing Solutions, Inc. page 52

53 EIM Maturity Model Redundant, undocumented data. Disparate databases without architecture. Little or no business metadata. Diverging semantics. Minimal data integration.. Minimal data cleansing. Dependent on a few skilled individuals. Responsibilities assigned across separate IT groups. Few defined IT roles. Some commonly used approaches but with no commitment to their use. Some management awareness, but no enterprise-wide buy-in. Little or no business involvement, no defined business roles. General purpose tools used as point solutions. Reactive monitoring and problem solving. Data regarded as a minor byproduct of business activity, with no estimated business impact. Level 1 Informal Processes Growing intuitive executive awareness of the value of data assets in some business areas. Initial forays in data stewardship and governance but roles are unclear and not ongoing. Initial efforts to implement enterprise-wide management, but with contention across groups with differing perspectives. New skills requirements are recognized and addressed with training. Enterprise architecture and MME projects underway. Data Distribution Services are deployed as strategic solutions Some processes are repeatable. Level 2 Emerging Processes Active executive Involvement across the enterprise. Ongoing, clearly defined business data stewardship. Central EDM organization. Standard processes, metrics, and tools used enterprise wide. Enterprise data architecture guides implementations. Centralized metadata management. Quality SLA s are defined and monitored regularly. Commitment to continual skills development. Periodic audits and proactive monitoring. Level 3 Engineered Processes Measurable process goals are established for each defined process Measurements are collected and analyzed. Quantitative (measurement) analysis of each process occurs Beginning to predict future performance Defects are proactively identified and corrected. Level 4 Controlled Processes Quantitative and qualitative understanding used to continually improve each process. Understanding of how each process contributes to the business strategies and goals of the enterprise. Level 5 Optimizing Processes Copyright EWSolutions 2006 All Rights Reserved 2007 Enterprise Warehousing Solutions, Inc. page 53

54 EIM Assessment Model Environmental Elements Activities Activities & Deliverables Deliverables Roles Roles & Organizations Organizations Practices Practices & Metrics Metrics Technology Technology Skills Skills & Training Training Culture Culture Functions Level 1 Informal Processes Level 2 Emerging Processes Level 3 - -Engineered Processes Level 4 - Controlled Processes Level 5 - Optimizing Processes Data Governance Information Architecture Metadata Management Information Security Management Information Quality Management Reference & Master Data Management Maturity Levels Data Warehousing & Business Intelligence Structured Data Management Unstructured Data Management 2007 Enterprise Warehousing Solutions, Inc. page 54

55 EIM Maturity Model LEVEL 1 LEVEL 2 LEVEL 3 LEVEL 4 LEVEL 5 DATA GOVERNANCE INFORMATION ARCHITECTURE METADATA MANAGEMENT INFORMATION SECURITY MANAGEMENT INFORMATION QUALITY MANAGEMENT REFERENCE AND MASTER DATA MANAGEMENT DATA WAREHOUSING AND BUSINESS INTELLIGENCE MANAGEMENT STRUCTURED DATA MANAGEMENT UNSTRUCTURED DATA MANAGEMENT 2007 Enterprise Warehousing Solutions, Inc. page 55

56 Assessment, Target Definition and Transition Planning 1 = Informal Processes 2 = Emerging Processes 3 = Established Processes 4 = Measured Processes 5 = Optimizing Processes Data Governance Information Architecture Meta Data Management Skills & Training Culture Activities & Deliverables Information Security Management Information Quality Management Technology Roles & Organizations Reference & Master Data Management DW & BI Management Structured Data Management Practices & Metrics Unstructured Data Management Assess where you are now and compare with where you want to be, then plan your roadmap of how you will reach the desired future state Enterprise Warehousing Solutions, Inc. page 56

57 EIM Maturity Assessment & Target Definition LEVEL 1 LEVEL 2 LEVEL 3 LEVEL 4 LEVEL 5 DATA GOVERNANCE C T U A INFORMATION ARCHITECTURE R R R G E METADATA E MANAGEMENT N T T INFORMATION SECURITY MANAGEMENT O S B INFORMATION QUALITY MANAGEMENT T J A E REFERENCE AND MASTER DATA MANAGEMENT T C E T DATA WAREHOUSING AND BUSINESS I INTELLIGENCE MANAGEMENT V STRUCTURED EDATA MANAGEMENT UNSTRUCTURED DATA MANAGEMENT 2007 Enterprise Warehousing Solutions, Inc. page 57

58 EIM Roadmap Methodology Assessment Where Are We Today? Deployment Make It So! Target Definition Where Do We Want To Be? Socialization Are We All On Board? Transition Planning How Do Get There? 2007 Enterprise Warehousing Solutions, Inc. page 58

59 Managing Information Assets Information is an enterprise asset managing it helps you stay ahead of the wave which may be a tsunami 2007 Enterprise Warehousing Solutions, Inc. page 59

60 Questions 2007 Enterprise Warehousing Solutions, Inc. page 60

61 Contact Information John Faulkenberry EWSolutions 15 Spinning Wheel Road, Suite 330 Hinsdale, IL Cell: Office: Enterprise Warehousing Solutions, Inc All Rights Reserved 2007 Enterprise Warehousing Solutions, Inc. page 61