‘reliable business data – ‘implementing a...
TRANSCRIPT
©2007-2016 Axis Software Designs, Inc. All Rights Reserved
‘Reliable Business Data –
‘Implementing A Successful
Data Governance Strategy
with Enterprise Modeling
Standards’
Welcome! Let Me Introduce Myself…
Marcie Barkin Goodwin
President & CEO
Axis Software Designs
www.axisboulder.com
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A Brief Bio of Marcie
Axis Software Designs – a consulting and product development company specializing in enterprise modeling standards, procedures and best practices.
Senior Enterprise Architect, providing modeling infrastructure consulting services and data modeling training to private industry and government agencies for over 25 years.
Designer of ‘EM-SOS!™’ – Enterprise Modeling Set of Standards
Partner – Sandhill Consultants
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Agenda
The Big Picture – Data Governance What Is It & Why Do We Need It? The Cost of Unreliable Business Data Data Governance in Modeling Best Practices
DAMA DMBOK/DMM Perspective
A Strategy for Reliability – Modeling Best Practices Properties of Reliable Data Standardized Data Design Practices & Oversight
Communication & Metadata Integrity (Who Can You Trust?) Reusability (Saving Time & Money) Reduce Redundancy (Say Again?)
Reliable Business Data in Action Best Practices - The Essentials
Strategy, Standards and Procedures Implementing a Standards & Best Practices Framework
We Know It’s Important, But Who Has Time?
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The Big Picture – Data Governance In Modeling
As in life, as in our IT & Modeling environments…
Enter Governance.
IT Governance, including Data Governance, is a
philosophy of accountability, substantiated by a
structured plan to guide IT processes towards
accurate and accessible information.
“It’s astonishing, in this world, how things don’t turn out at all the way you expect them to.”
Agatha Christie
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Data Governance – What Is It?
“Data Governance is the formal orchestration of people, processes, and technology to enable an organization to leverage data as an enterprise asset.” – MDM Institute
“Information Governance is the specification of decision rights and an accountability framework to encourage desirable behavior in the valuation, creation, storage, use, archival and deletion of information. It includes the processes, roles, standards and metrics that ensure the effective and efficient use of information in enabling an organization to achieve its goals.” – Gartner
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Data Governance – Why Do We Need It?
…Because generally speaking, the management and
quality of our data is sorely lacking.
The costs of managing disparate IT assets is expensive and the work efforts are cumbersome
Data processes aren’t consistent and standardized, thus creating different report results
Regulatory compliance - Sarbanes-Oxley, etc.:
“Where management has outsourced…functions to third party service provider(s), management maintains a responsibility to assess the controls over the outsourced operations.”
AND – ‘On average, American companies believe that 25% of
their data is inaccurate.’ Survey: ‘Experian Quality Data’
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Unreliable Business Data
Rarely do organizations design from an enterprise
perspective, and as a result they ‘sub optimize’ solutions
by allowing diverse standards, naming conventions,
codes, etc.
This ‘silo’ approach to data and modeling efforts results
in data inconsistencies which have a deleterious effect
on the overall understanding, accessibility, integration
and reliability, or integrity of the data.
And other problems exist as well… ©2007-2016 Axis Software Designs, Inc. All Rights Reserved page 9
Unreliable Business Data (Cont.)
Tendency to clone multiple, non-standardized versions of data structures resulting in: Unreliable answers from data analysis Variable data structures that are non-reusable, inconsistent,
inflexible and expensive to fix
Lack of enforcement exists for: Naming standards and class words Business dictionaries & abbreviations
Overruns of Application Development schedules and budgets
Lack of Business to Data Traceability
Difficulties with Data Integration & Interoperability
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Regulatory
Economic Disaster
Sept 9, 2010 San
Bruno, CA
Public Health & Safety
The absence of well documented standards, common business term definitions, and an agreed-to format for exchange makes it almost impossible for parties to understand each other.
The Cost of Unreliable Business Data
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Do These Issues Look Familiar?
Same object name has different definitions and usage Expensive conflicts in processes Inaccurate and risky decision making
Siloed metadata (turf wars) Unnecessary duplication and cost due to ambiguity in meaning and
usage
Same object definition applied to different names Higher rates of redundancy and data errors
Inconsistent meaning across lines of business Reduced value of BI
Reduced opportunity for re-use Increased cost and time to market, decreased quality and value
Change and growth management difficult to impossible Lost opportunity, increased cost of doing business
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Data Governance in Modeling Best Practices Data modeling Best Practices support the objectives
of data governance and produce reliable business data.
Develop Roles and Responsibilities including data custodians
Develop standards for model and model object naming
Develop standardized procedures regarding how models are to be created, organized, stored, changed, archived, backed up, versioned and migrated through a model development life cycle
Develop audit procedures that ensure ongoing compliance with standards, business rules and/or government regulations
A Best Practices strategy prevents the risk of creating incorrect data which may result in critical harm in the real world.
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Blueprints - DAMA DMBOK & CMMI DMM
The DAMA-DMBOK2 Guide Knowledge Area Wheel
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Data Management Maturity Model
Properties of Reliable Data
Consistency of: Meaning Usage Form (Datatype, etc.) Interface Results
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For data to be reliable, it must be consistent and usable across all time, space and function of the owning organization. It can be characterized by some or all of the following properties:
Predictable Measureable Enforceable Manageable Portable Reusable
Standardized Data Design Practices & Oversight A modeling strategy which incorporates an enterprise perspective is key to ensuring the reliability of business data.
Strategies are determined by clarifying where you are, and determining where you want to be
Strategies are not ‘one size fits all’, but they do share the critical goals of: Communication – the all-important foundation Metadata Integrity “The naked truth is always better than the best-dressed lie.” Ann Landers Reusability - The reuse of model objects, brings
consistency to model structures Non-Redundancy - Redundancy is one of the most
common causes of inefficiency & data inaccuracy. ©2007-2016 Axis Software Designs, Inc.
All Rights Reserved page 16
Reliable Business Data in Action
When an organization manages its data as a corporate asset, and makes modeling best practices a part of its data governance efforts, the focus turns towards the business value of the data, not just the IT requirements.
The business drivers for managing data as a corporate asset are:
Competitiveness
Regulatory compliance
Realizing the benefit of investments in BI and other information-based initiatives
Risk mitigation ©2007-2016 Axis Software Designs, Inc. All Rights Reserved page 17
Reliable Business Data in Action (Cont.)
The keys to successful best practices modeling implementation are:
Management support of a data governance program,
including an integral best practices approach to modeling
Development of a modeling strategy that builds governance
and quality into the process
Involvement by both the business side as well as IT
Resistance to creating or accepting silos of standards and
procedures
Development of a ‘Model Management Framework’ to
support the modeling strategy
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A Modeling Framework
Must support:
Strategic goals & policies of the organization
Standards – which are extensible across the enterprise
Processes & Data Modeling Life Cycle – to ensure repeatable, efficient data design and outcomes
Data Governance Roles & Responsibilities
Must include:
Audit documentation – for changes in processes & content
Metrics Reports – to measure improvement in the data design process (reuse, decreased redundancy)
Must be:
Easily accessible, maintained & enforced
Multi-user environment with associated permissions ©2007-2016 Axis Software Designs, Inc. All Rights Reserved page 19
The Challenges
Organizations generally understand the need for modeling
standards and procedures, but face several obstacles in
getting the job done:
There isn’t a plan for developing a Framework
In-house resources are already working full time
Resources may not have infrastructure knowledge or writing skills
Internal politics or ‘silo groups’ can’t agree on what should be implemented
“We know we need it, but who has the time?”
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A Modeling Framework Buy vs Build? DMBOK/DMM
A great blueprint of what is needed
The details need to be defined
Buy vs Build
Time
Money
Expertise (quality of the result)
Consistency across the organization
Acceptance and buy-in
Business
IT
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Critical Framework Content List
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Procedures Administrative Change Control Data Object Promotion Issue Resolution Logical DM Submission &
Deliverables Model Backup Model Change Control Model Creation & Population New User – Model Repository Notification & Update Physical DM Submission &
Deliverables Stewardship Synchronization Versioning
Standards Classword – Domain – Datatype List Color Themes Data Object Definitions Guidelines Library Structure & Naming Model Repository Profiles Physical Model Object Naming User Defined Properties
Critical Framework Content List
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Blueprints for Enterprise Model Development
Building an Enterprise Data Model
Data Model Life Cycle DMLC Top Level
DMLC Detailed View
Shared Data Object Creation
Agile (Iterative)
Data Architecture -Development Integration
DMLC Definitions
Model Quality Reports Basic Model Metrics & Reuse
Glossaries Glossary
Templates Template Usage
Forms Administrative Change Control Form Logical Data Model Check List Model Change Control Form New User Repository Profile Form Physical Data Model Check List
Implementing a Standards & Best Practices Framework
Key Steps
Understanding ‘Where you are’ – Gap Analysis Assessment
Using Assessment to define a strategy – Compare to known ‘Best Practices’ guidance & solutions
The Decision: Buy vs Build
Collaborate on a Tactical Plan – Engage the stakeholders
Integrate with overarching Data Governance & Management initiatives
Develop a Proof of Concept – Prototype/Pilot
Deploy, Check & Adjust (If necessary)
Communicate, Educate & Align throughout the Implementation (especially between Business & IT)
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Benefits of A ‘Buy’ Solution
Supports Data Governance principles & requirements
Supports any Data Model Life Cycle methodology
(Waterfall, Agile, etc.)
Solves the problem of requiring in-house resources to
analyze & write necessary standards documentation
Compatible with the company’s data modeling solution
Implemented on the company’s intranet for accessibility
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Standard Classwords implemented using ERwin Domains with inheritance
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DMM – Framework Mapping
1 Performed
Ad Hoc localized Standards
2 Managed Top Level Data Management Life Cycle (DMLC) Naming Standards Automated Templates Standards Training
3 Defined Detailed cross functional DMLC Standard processes and milestones Standardized health checks
Maturity
Business Value
4 Measured
Product and process metrics Change management and process improvement based on metrics
5 Optimized Adaptive DMLC (Agile) Global deployment of EM-SOS! Data Object Collections and Repository Global Shared Data Objects and Reuse
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Modeling Environment
Assessment
Axis offers a comprehensive assessment incorporating a strategy which centers on the reuse and non-redundancy of data structures within an organization.
This short term consulting engagement analyzes the customer’s current modeling environment and delivers a ‘Findings and Recommendations’ document delivering analysis and specific recommendations for streamlining and improving the modeling infrastructure.
You can start by conducting a ‘Standards Self Check’ at: http://www.sandhillconsultants.com/emsos.asp
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Contact Information
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[email protected] 303-981-6525
For information, please contact:
Robert Lutton
416-219-4504