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Presentation Overview
� Current State Challenges & Impact
� Proposed Solution & Approach
� Critical Success Factors
2
� Next Steps
Current State Data ChallengesFrom the Business Perspective…
Data ChallengesImpactedCapabilities
Unknown Data Existence
� Organization not aware of all data at its disposal� Some data not even inventoried� Documentation is lacking� Confusion around where to go for certain data
Operations Agility and Reporting
Unknown Data Meaning� Content and meaning of data not fully known� Data not thoroughly understood
� Record key integrity Reporting
Inadequate / Inflexible Data Structures
� Record key integrity� Referential integrity� Cardinality integrity� Insertion/deletion anomalies� Duplicate or lost entities� Current design does not meet information requirements
Data Inconsistencies � Data is defined differently across applications� Multiple formats for same data elements � Different meanings for the same code value � Multiple codes values with the same meaning
Risk Managementand SecurityInvalid Data Content
� Missing data� Wrong data (no constraints applied)� Data outside defined domain (overloaded columns)
Security / Access Control � Data propagation increases risk of exposure & data leakage
3
Data ChallengesImpactedCapabilities
Lack of Planning and Roadmap
� No common vision and prioritization for data� Big picture / long-term view not well understood� No data sourcing (authoritative source) strategy� Prioritization and investment model not defined
Data Redundancy
� Waste of space to have duplicate data� Causes more maintenance head aches
Current State Data ChallengesFrom the IT Perspective…
IT Efficiency
Data Redundancy� Causes more maintenance head aches� Data changes in one file could cause inconsistencies� Compromises data integrity
Lack of Governance & Stewardship (Process & Data)
� Lack of coordination and central control� Inadequate data responsibility clearly defined� No single point of contact for issue resolution� Different applications handle data differently� Ambiguous business rules defined� Non-standard file formats� Limited data sharing
Program-Data Dependence
� Each application maintains it’s own data� Each application program needs to include code for it’s own metadata� Each application program must have its own processing routines for
reading, inserting, updating, and deleting data
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Result of the Current Environment
� DATA CANNOT BE READILY IDENTIFIED
� DATA UNDERSTANDING INHIBITED
� LIMITED AWARENESS OF DATA RESOURCE
� LIMITED DATA SHARING ACROSS BUSINESS FUNCTIONS
� POOR BUSINESS UNDERSTANDING
INAPPROPRIATE USE OF DATA� INAPPROPRIATE USE OF DATA
� INAPPROPRIATE BUSINESS ACTIONS & DECISIONS
� IMPACTS ON BUSINESS AND PEOPLE
� LOST PRODUCTIVITY OF AGENCY CUSTOMERS & IT STAFF
� STAFF SPENDS MAJORITY OF TIME VERIFYING DATA INSTEAD OF ANALYZING IT
5
The Cause…Disparate Data Cycle
A self-perpetuating cycle where disparate data continue to be produced at an ever-increasing rate because people rate because people
� do not know what data exist, or � do not want to use it because
they don’t understand it, or � can’t trust it.
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Why Change is Needed The Way Forward The Payoff
Breaking the Cycle…A framework for enabling the Business
BUSINESS DRIVERS
� Agility � Ability to introduce new functionality /
#1� Data is correct� Data is accurate� Data is consistent� Data is complete� Data is integrated � Data values follow the business rules� Data corresponds to established domains
� Data is well defined and understood
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� Ability to introduce new functionality / capability in a timely manner
� Risk Management � Gain better control over data environment
� IT Efficiency � Reduce / eliminate inefficiencies + decrease complexity
� Data is well defined and understood� Program-data independence� Planned data redundancy� Improved data consistency� Improved data sharing� Increased application development productivity
� Enforcement of standards� Improved data quality� Improved data accessibility and responsiveness
� Reduced program maintenance� Improved decision support
High-Level Process
Obtain Executive Buy-In and
Support Establish
Management Structure
and Control
Define an
Maintain the Architecture
1
2
8
8
Define an Architecture Process & Approach
Develop Baseline
Data Architecture
Develop Target Data Architecture
Develop th e Transition
Plan
Use and Monitor the Architecture
Governance (Control & Oversight)
3
4
5
6
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GOVERNANCE
METADATA MANAGEMENT
What data assets do we have and how are they being used (context) today (by whom and when), with what tools?
What process, people, technology, standards, and governance do we need to leverage our data asset?
Dat
a A
rchi
tect
ure
Defining the Data Architecture
OPERATIONAL ENABLEMENT
DECISION SUPPORTWhat are the key business questions that drive decision making, and what data is needed to answer them?
How should data be organized, persisted, and/or distributed in support of business operations?
Key
Com
pone
nts
of D
ata
Arc
hite
ctur
e
9
Components Primary Concerns
What data assets (per classification) do we have an d how are they being used (context) today (by whom and when)?
Who is responsible (steward) for what data?
3
5
What process, people, technology, standards, and governance do we need to leverage the data asset?
What (and where) is the authoritative source of dat a?4
1
Ste
war
dshi
p
Roa
dmap
Vision
Inventory
Ownership
Sourcing
2What cross-organizational structure is required to ensuredata decisions are being made consistently (in alignmen twith the Bank’s strategy)?
FrameworkProcessGOVERNANCE
METADATA
Key Artifacts
Data Catalog
Data Steward Directory
Data Store Classification
Data Strategy & Roadmap
Governance Framework & Process
View
Addressing the Right Things…
Analysis
Where should data be reported from (with what tools )?
5
6
7
8
11 What are the key business questions that drive the Bank, and what data is needed to answer them?
Per
sist
ence
Org
aniz
atio
n
Dis
trib
uti
on
Reporting
9
12
Ste
war
dshi
p
Roa
dmap
Governance
Access & Security 10
How should data be organized (designed / modeled)?
Where should data be persisted (stored)?
In what order should replicated data be updated?
How should data be accessed/secured (in different locations)?
How should data be distributed (replicated)?OPERATIONAL ENABLEMENT
DECISION SUPPORT
Enterprise Data Model & Standards
Data Management Plan
Data Distribution Strategy
Business Intelligence Roadmap
Operational Update Patterns
Enterprise Reporting Strategy
Data Access Policy and Standards
10
Maturing the CapabilityMoving the Needle…
Chaotic Reactive Proactive Service Optimizing
InformalProcesses
DisciplinedProcesses
StandardProcess
PredictableProcess
“Self” ImprovingProcess
Manual, inconsistent methods that are not repeatable
Course corrections are applied in certain cases, over time
Methods improve and gain consistency with understanding & use
Improvements arepredictable, proven, andintentionally created
Repeatable methodscreate opportunities forefficiencies & economiesof scale
Data Driven Information Driven Knowledge Driven
Application Focused Departmental Focused Enterprise Focused
Stage I Stage II Stage III Stage IV Stage V
Foc
usM
atur
ity
11
Application Focused Departmental Focused Enterprise Focused
DB Operations, Physical DB Design Enterprise Model, Data Catalog Governance
Data Support Data Development Data Stewardship Data IntegrationEnterprise Data Program
Management
� Operations� Tuning� Maintenance� Backup/recovery� Archiving
� Requirements Analysis
� Modeling� Design� Implementation
Identification, definition,specification, sourcing, and standardization of all data across all LOBs within a specific subject area (e.g., customer)
Identification, modeling, coordination, organization, distribution, and architecting of data shared across business areas or the enterprise
Definition, coordination, implementation, and monitoring of enterprise data managementvision, goals, organization, processes, policies, plans, standards, metrics, audits, and schedules
Asset Ignorance Asset Recognition Leveraged Assets
Roa
dmap
Foc
us
Initial Transitional Goal
The Plan…
Track IIIGOVERNANCE
Track IIARCHITECTURE
TRACK I
People1. Establish Decision Rights
and Checks-and-Balances
2. Establish Accountability
3. Stakeholder Support
Process1. Stewardship
2. Manage Change
3. Resolve Issues
Communication1. Stakeholder
Communications
2. Measuring and Reporting Value
Policy1. Align Policies,
Requirements, and Controls
Technology1. Outline Acceptable
Technology and Tools Usage
2. Data Management Tools
Metadata1. Define Enterprise Metadata
2. Specify Data Quality Requirements
People1. Establish Decision Rights
and Checks-and-Balances
2. Establish Accountability
3. Stakeholder Support
Process1. Stewardship
2. Manage Change
3. Resolve Issues
Communication1. Stakeholder
Communications
2. Measuring and Reporting Value
Policy1. Align Policies,
Requirements, and Controls
Technology1. Outline Acceptable
Technology and Tools Usage
2. Data Management Tools
Metadata1. Define Enterprise Metadata
2. Specify Data Quality Requirements
Key
Com
pone
nts
Track IPLANNING
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Transformation Plan Future StateCurrent State Stewardship
Identify Major Milestones and Dependencies Crucial to Implementing Future State Architecture
Identify Data Reqs ; Sourcing; Master Data Stores; Interfacing; How Data is Accessed & From Where
Inventory Current State Assets and Data; Document Context & Semantics
Establish Governance Structure; Identify Ownership and Accountability of Data Assets; Monitor & Report
Charter & Plan
Identify Key Participants; High Level Requirements; Goals & Objectives; Desired Outcome and Plan
Hig
h-Le
vel I
tera
tive
App
roac
h
Prioritization & Roadmap
Data Governance
Program Management
Asset Guidance
Draft and Publish Data Management Policies & Standards
Policies & Standards
Communication & Education
Prepare & Conduct Training; Mentor IT & Business Staff
Training Data / Information Architecture
Continuous Improvement Iterative Process
Data Governance Framework
1. Strategy 2. executed by “People” 4. ensures accurate “Data” through “Policies”
2. 0 Data Governance Council
2. 1 Data Stewards
working with
to serve
4.0 Data Assetsare consistent through
4.1 Rules & Standards
4.3 Compliance 4.2 Policies
driven fromto ensure
and
“ Strategy” executed by “ People” through a set of integrated “ Processes” ensures accurate “ Data” through “ Policies” enabled by “ Technology”
3. through a set of integrated “Processes” 5. enabled by “Technology”
1.0
Str
ateg
y an
d M
issi
on
1.1
Org
aniz
atio
n an
d P
lann
ing
2. 2 Data Stakeholders
to serve
3. 0 Meetings and Communications
3. 1 Decision Rights and Controls
3. 2 Roles and Responsibilities
establishing
operated via
4.4 Data Quality 4.5 Performance Metrics
andmonitored through
5.0 Business Intelligence Applications
5.1 Data Warehouses and Integration Tools
5.2 Master Data and Metadata
5.3 Data Quality Tools
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Data Governance Structure
Executive Leadership
Executives authorize solutions and provide issue resolution —even if they impact organizational structure or project costs and timelines.
Stewards and Content Managers represent the Business community. They work with dedicated governance managers through processes that administer data based on business rules.
• Create standard definitions for data.
• Establish authority to create, read, Governance managers
Stewardship/Quality Management
Governance
Proactive &
Responsive Processes
• Establish authority to create, read, update and delete data.
• Ensure consistent and appropriate usage of data.
• Provide SME in the resolution of data issues
Governance managers are responsible for the development and implementation of the policies, guidelines, and standards for managing the corporation’s data.
14
Critical Success Factors
� Executive Management Commitment & Support
� Availability of Technical Resources
� Availability of Business/Data SMEs
� Data Management (Metadata) Tools and Repository� Data Modeling Toolset
15
� Business Process Modeling Toolset
� Data Discovery and Dictionary Toolset
� Empowerment to Enforce Approved Data Policies & Standards
Next StepsMaking it Happen…
� Identify Key Participants� Identify Steering Committee
� Identify Working Group Participants
� Hold First Working Session� Establish Recurring Schedule
� Draft Program Charter
TentativeTimeline
45 Days
30 Days
16
� Draft Program Charter� Determine business drivers & requirements
� Develop vision and objectives
� Develop guiding principles
� Submit Charter to Steering Committee for Approval
� Document Current State (v1.0)
� Draft Phase I Recommendation & Plan
� Present Recommendation & Plan to Steering Committee for Approval
45 Days
90 Days
60 Days
