EWSolutions
Enterprise Business
Intelligence Solutions
Presented to DAMA Wisconsin
April 12, 2007
by John Faulkenberry
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:
For more information on our Consulting Services or World-Class Training,
call toll free 866.EWS.1100, (866.397.1100), the main number 630.920.0005, or email us at Info@EWSolutions.com
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
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)
Dat a St ew ar dshi p Structured Data Management Unstructured Data Management Reference & Master Data Management Data Warehousing & Business Intelligence Information Quality Management Data Governance Information Architecture Information Architecture
Meta Data Management Meta Data Management Information Security Management
Transaction Business
Reference & Unstructured &
EWSolutions
Clients
Driehaus Capital
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
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).
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.
DW/BI Architecture
Data
Warehouse
Staging
Area
Data Mart
Business
Intelligence
Environment
Information
Source
Systems
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
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
DW/BI Design Concepts
Dimensional Data Marts
¤
Fact Tables & Dimension Tables
¤
Star Schemas & Variations
¤
Shared Dimensions
9,624
6,553
Org
Geo
Chan
???
Time
Prod
Data Mart
DW/BI Design Concepts
Dimensional Data Warehouse
Enterprise Data Warehouse
¤
Dependent Data Marts
Data
Warehouse
Data
Warehouse
DW/BI Architecture
Data
Warehouse
Staging
Area
Data Mart
Data Marts
Data
Warehouse
Business
Intelligence
Environment
Information
• Ad Hoc Query & Reporting • Enterprise Reporting • Multi-Dimensional Analysis • Statistical Analysis • Data Mining • What-If Modeling • Analytics • Dashboards & ScorecardsSource
Systems
DW/BI Enabling Technology & Processes
Data Modeling
Extract, Transform, and Load (ETL)
Data Profiling
Data Cleansing
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
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
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
Enterprise BI Approaches
Integrated Enterprise Master Plan
vs. Independent Data Marts
Operational
Applications
Islands
of Data
Reporting
Systems
Claims Pharmacy Financial AnalysisHealth & Medical Services (CQM, HSA)
Actuarial & Underwriting Analysis Sales & Mktg / Network Development Utilization Membership/Enrollment & Billing Standard Adhoc Standard Adhoc Standard Adhoc Standard Adhoc Standard Adhoc Standard Adhoc Standard Adhoc Standard Adhoc North E/B TOPPS ES-9000
IPS- Inter Practice SystemVAX(Burlington) PSIMED HPE-980
MGD ClaimsAS/400 Query
Pharmacare (outside vendor)AS/400 Pharmaview (outside vendor)
NED E/B
ACPS- Automatic Claims Processing System PASS - Patient Appointment Scheduling System ENCOUNTER FFS - Fee For Service REF - Referrals HP-992 NEDClinical Computer Pharmacy DB Provider Master AMISYS MARS •Hospital Summary •Quality Assurance Request
HP (9 series) •Network & Medical Request •Actuarial End User Request •Claims
Prov DB Drug DB
AMRS-Advanced Medical Record System RIS- Radiology Information System
LAB/LIS- Laboratory Information System
VAX Cluster RX42 HPE-980
MHUM - Mental Health Utilization Management
AST 486 server
HealthchexPentium PC Bulletin Board System (BBS)
NED DatawarehouseHP937 HSA dept. Lan Server
NED Multiview GL and AP
PHC Pharmacy Server PHC Actuarial Analysis Server Analytic Database
Quantum Dec Alpha MAMSYS/PAPSYS PHC JV Finance Server PHC Network Development Server
PHC Medical Services Server PHC Multi-view GL.
(14) Foxpro Applications ASAP - Actuarial System Analysis Program
MS SQL Server
DB2 and SAS dataset Decision Analyzer
GL
SAS , SAS screens, Viewpoint GMIS-Claim Check Actuarial SAS dataset
ES-9000
Medical Groups
HCD MGDLegend NED PHC Multiple colors indicate the system is used by multiple divisions.
Operational
Applications
Islands
of Data
Reporting
Systems
Claims Pharmacy Financial AnalysisHealth & Medical Services (CQM, HSA)
Actuarial & Underwriting Analysis Sales & Mktg / Network Development Utilization Membership/Enrollment & Billing Standard Adhoc Standard Adhoc Standard Adhoc Standard Adhoc Standard Adhoc Standard Adhoc Standard Adhoc Standard Adhoc North E/B TOPPS ES-9000
IPS- Inter Practice SystemVAX(Burlington) PSIMED HPE-980
MGD ClaimsAS/400 Query
Pharmacare (outside vendor)AS/400 Pharmaview (outside vendor)
NED E/B
ACPS- Automatic Claims Processing System PASS - Patient Appointment Scheduling System ENCOUNTER FFS - Fee For Service REF - Referrals HP-992 NEDClinical Computer Pharmacy DB Provider Master AMISYS MARS •Hospital Summary •Quality Assurance Request
HP (9 series) •Network & Medical Request •Actuarial End User Request •Claims
Prov DB Drug DB
AMRS-Advanced Medical Record System RIS- Radiology Information System
LAB/LIS- Laboratory Information System
VAX Cluster RX42 HPE-980
MHUM - Mental Health Utilization Management
AST 486 server
HealthchexPentium PC Bulletin Board System (BBS)
NED DatawarehouseHP937 HSA dept. Lan Server
NED Multiview GL and AP
PHC Pharmacy Server PHC Actuarial Analysis Server Analytic Database
Quantum Dec Alpha MAMSYS/PAPSYS PHC JV Finance Server PHC Network Development Server
PHC Medical Services Server PHC Multi-view GL.
(14) Foxpro Applications ASAP - Actuarial System Analysis Program
MS SQL Server
DB2 and SAS dataset Decision Analyzer
GL
SAS , SAS screens, Viewpoint GMIS-Claim Check Actuarial SAS dataset
ES-9000
Medical Groups
HCD MGDLegend NED PHC Multiple colors indicate the system is used by multiple divisions.
Claims Pharmacy Financial Analysis
Health & Medical Services (CQM, HSA)
Actuarial & Underwriting Analysis Sales & Mktg / Network Development Utilization Membership/Enrollment & Billing Standard Adhoc Standard Standard Adhoc Adhoc Standard Adhoc Standard Standard Adhoc Adhoc Standard Adhoc Standard Standard Adhoc Adhoc Standard Adhoc Standard Standard Adhoc Adhoc Standard Adhoc Standard Standard Adhoc Adhoc Standard Adhoc Standard Standard Adhoc Adhoc Standard Adhoc Standard Standard Adhoc Adhoc Standard Adhoc Standard Standard Adhoc Adhoc North E/B North E/B TOPPS ES-9000
IPS- Inter Practice SystemVAX(Burlington) IPS- Inter Practice SystemVAX(Burlington) PSIMED HPE-980
MGD ClaimsAS/400 QueryMGD Claims AS/400 Query
Pharmacare (outside vendor)AS/400 Pharmaview (outside vendor) Pharmacare (outside vendor)AS/400 Pharmaview (outside vendor) Pharmaview (outside vendor)
NED E/B NED E/B
ACPS- Automatic Claims Processing System ACPS- Automatic Claims Processing System PASS - Patient Appointment Scheduling System PASS - Patient Appointment Scheduling System ENCOUNTER ENCOUNTER FFS - Fee For Service FFS - Fee For Service REF - Referrals REF - Referrals HP-992 NEDClinical Computer Pharmacy DB Pharmacy DB Provider Master Provider Master AMISYS MARS •Hospital Summary •Quality Assurance Request
HP (9 series) •Network & Medical Request •Actuarial End User Request •Claims
Prov DB Drug DB
AMRS-Advanced Medical Record System RIS- Radiology Information System LAB/LIS- Laboratory Information System VAX Cluster AMRS-Advanced Medical Record System RIS- Radiology Information System
LAB/LIS- Laboratory Information System
VAX Cluster RX42 HPE-980
MHUM - Mental Health Utilization Management
AST 486 server
MHUM - Mental Health Utilization Management
AST 486 server
HealthchexPentium PC HealthchexPentium PC Bulletin Board System (BBS) Bulletin Board System (BBS)
NED DatawarehouseHP937 NED DatawarehouseHP937 HSA dept. Lan Server HSA dept. Lan Server
NED Multiview GL and AP NED Multiview GL and AP
PHC Pharmacy Server PHC Actuarial Analysis Server PHC Actuarial Analysis Server Analytic Database Analytic Database Quantum Dec Alpha Quantum Dec Alpha MAMSYS/PAPSYS MAMSYS/PAPSYS PHC JV Finance Server PHC Network Development Server PHC JV Finance Server PHC Network Development Server PHC Network Development Server
PHC Medical Services Server PHC Medical Services Server PHC Multi-view GL. PHC Multi-view GL.
(14) Foxpro Applications (14) Foxpro Applications ASAP - Actuarial System Analysis Program
MS SQL Server ASAP - Actuarial System Analysis Program
MS SQL Server
DB2 and SAS dataset Decision Analyzer
GL
SAS , SAS screens, Viewpoint GMIS-Claim Check Actuarial SAS dataset
ES-9000 DB2 and SAS dataset DB2 and SAS dataset Decision Analyzer Decision Analyzer
GL
SAS , SAS screens, Viewpoint GMIS-Claim Check GMIS-Claim Check Actuarial SAS dataset Actuarial SAS dataset
ES-9000
Medical Groups
HCD MGDLegend NED PHC Multiple colors indicate the system is used by multiple divisions. HCD
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
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
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
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
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
Subject Area Model – example showing subjects and simple
relationships between subjects
Enterprise Data Modeling
Sales
Order
Accounts
Receivable
Purchase
Order
Customer
Supplier
Accounts
Payable
Deceptively simple – but difficult to identify subjects and agree
upon terminology across multiple business units!!
Inventory
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
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
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
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
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
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
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
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).
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
Managed Metadata Environment
Metadata Sourcing Layer
Metadata Sourcing Layer
Metadata
Extract
Metadata
Repository
Messaging/Transactions (EAI, web services, XML, etc.)
Software Tools
Metadata Delivery Layer
Metadata
Management Layer
Documents/Spreadsheets
End Users (business and technical) Third Parties (business partners, vendors,
customers, government agencies) Metadata Extract Metadata Extract Metadata Extract Metadata
M
e
t
a
d
a
t
a
I
n
t
e
g
r
a
t
i
o
n
L
a
y
e
r
Data Warehouse/ Data Mart(s) Websites/E-CommerceThird Parties (vendors, customers, government agencies)
Metadata Marts
End Users
(business and technical) Business Users
Applications (CRM, ERP, etc.)
End Users
(business and technical)
Websites/ E-Commerce Applications
(CRM, ERP, data warehouses, etc.) Metadata Extract
Messaging/Transactions (EAI, web services, XML, etc.)
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
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
Data Governance Organizations
• Business Data Stewards • Coordinating Data Stewards Strategic
Tactical
Operational – by Subject Area, not by LOB
• Executive Data Stewards
< 20% < 5%
80-85% Conflicts Resolved
at this level
Data Governance Council
Data Stewardship Teams Data Stewardship Committee
E
sc
a
la
tio
n
P
a
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
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 Functional Framework
Data Stewardship
Structured
Data
Management
Unstructured
Data
Management
Reference &
Master Data
Management
Data
Warehousing
& Business
Intelligence
Information
Quality
Management
Data Governance
Information Architecture
Meta Data Management
Information Security Management
Transaction
Data
Business
Intelligence
Data
Reference &
Master Data
Unstructured &
Semi-Structured
Data
EIM Services
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
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
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.”
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.
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
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
long-term enterprise focus while implementing
incrementally and iteratively.
EIM Roles
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
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
EIM Organizations
Information
Technology
CIO
Infrastructure
& Operations
Reporting Structures
Data Governance Council
Application
Engineering
EIM
Center of Excellence
Project
Management
Office
Business
Process
Engineering
• EIM Director • Data Architects • Data Modelers • Data Quality Analysts • Meta Data Administrators • Data Integration Architects • DW/BI Administrators • Database Administrators • Data Security Administrators• Executive Data Stewards • Chief Data Steward (chair) • EIM Leader (facilitator) • CIO (sponsor)
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
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
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
EIM Roadmap
Assessment
Where Are We Today?
Target Definition
Where Do We Want To Be?
Deployment
Make It So!
Transition Planning
How Do Get There?
Socialization
EIM Maturity Model
Level 1
Informal
Processes
Level 2
Emerging
Processes
• 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 by-product of business activity, with no estimated business impact.
• 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.
• 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
Level 4
Controlled
Processes
Level 5
Optimizing
Processes
• Measurable process goals are established for each defined process • Measurements are collected and analyzed. • • QuantitativeQuantitative (measurement) analysis of each process occurs • Beginning to predict future performance • Defects are proactively identified and corrected. •• Quantitative andQuantitative qualitative qualitative understanding used to continually improveeach process. • • Understanding of Understanding of how each process how each process contributes to the contributes to the business strategies business strategies and goals of the and goals of the enterprise. enterprise.
EIM Assessment Model
M
at
ur
ity
L
ev
el
s
Funct
ions
Environmental Elements
Act ivit ies & Del ivera bles Act ivit ies & Del ivera bles Role s & Organi zat ions Role s & Organi zat ions Prac tices & Me trics Prac tices & Me trics Technology Technology Skill s & T raining Skill s & T raining Cultu re Cultu re L e v e l 1 – In fo rma l Pr oce sses L e v e l 1 – In fo rma l Pr oce sses L e v e l 2 – E mer g in g Pr ocesses L e v e l 2 – E mer g in g Pr ocesses L e v e l 3 --Eng in eere d Pr ocess es L e v e l 3 --Eng in eere d Pr ocess es L e v e l 4 -C on tr o lle d Pr ocess es L e v e l 4 -C on tr o lle d Pr ocess es L e v e l 5 -O p timiz in g Pr ocesse s L e v e l 5 -O p timiz in g Pr ocesse s Data Governance Data Governance Information Architecture Information Architecture Metadata Management Metadata ManagementInformation Security Management
Information Security Management
Information Quality Management
Information Quality Management
Reference & Master Data Management
Reference & Master Data Management
Data Warehousing & Business Intelligence
Data Warehousing & Business Intelligence
Structured Data Management
Structured Data Management
Unstructured Data Management
