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DAMA-CDGA Data Governance Engineer-15. Data Management Maturity Assessment
Capability maturity assessment is a capability improvement plan based on the capability maturity model framework, which describes the process from the initial state of data management capabilities to optimization. When an organization meets the capability characteristics of a stage, its maturity level can be assessed and a plan can be developed to improve capabilities.
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DAMA-CDGA Data Governance Engineer-15. Data Management Maturity Assessment
- One Hundred Years of Solitude Character Relationship Chart
One Hundred Years of Solitude is the masterpiece of Gabriel Garcia Marquez. Reading this book begins with making sense of the characters' relationships, which are centered on the Buendía family and tells the story of the family's prosperity and decline, internal relationships and political struggles, self-mixing and rebirth over the course of a hundred years.
- One Hundred Years of Solitude Character Relationship Chart
One Hundred Years of Solitude is the masterpiece of Gabriel Garcia Marquez. Reading this book begins with making sense of the characters' relationships, which are centered on the Buendía family and tells the story of the family's prosperity and decline, internal relationships and political struggles, self-mixing and rebirth over the course of a hundred years.
- Project Management Process Template
Project management is the process of applying specialized knowledge, skills, tools, and methods to project activities so that the project can achieve or exceed the set needs and expectations within the constraints of limited resources. This diagram provides a comprehensive overview of the 8 components of the project management process and can be used as a generic template for direct application.
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- Outline
15. Data Management Maturity Assessment
introduction
Capability maturity assessment is a capability improvement plan based on the capability maturity model framework, which describes the process from the initial state of data management capabilities to optimization.
When an organization meets the capability characteristics of a stage, its maturity level can be assessed and a plan can be developed to improve capabilities.
When an ability shows characteristics that are inconsistent with the level, the level will be improved, but the ability levels have a set sequence and no level can be skipped.
include
Level 0
incapacity level
Level 1
initial or temporary level
Success depends on individual ability
level 2
repeatable level
Developed the most basic process rules
Level 3
level defined
Standards established and used
level 4
Already managed
Capabilities can be quantified and controlled
Level 5
Optimization level
Capacity improvement goals are quantifiable
business drivers
Supervision
Regulation imposes minimum maturity levels on data governance
data governance
Data governance requires a maturity assessment for planning and compliance purposes
Organizational readiness for process improvement
The organization recognizes that improving its practices should begin with an assessment of its current state
organizational changes
Organizational changes create data management challenges
new technology
Advances in technology provide new ways to manage and use data
Data management issues
For the problem to be solved, the organization hopes to evaluate its current status to make better decisions about implementation
goals and principles
The primary goal of a data management capability assessment is to assess the current state of data management activities in order to develop plans for improvements
Assessments place the organization on a maturity scale by analyzing specific strengths and weaknesses, thereby helping the organization identify, prioritize and implement improvement opportunities.
Introducing data management concepts, principles and practices to stakeholders
Clarify stakeholder roles and responsibilities regarding organizational data
Emphasize the need to manage data as a critical asset
Expand awareness of data management activities across the organization
Help improve the collaboration needed for effective data governance
basic concept
Evaluation levels and characteristics
Level 0
incapacity level
In data management, management activities or formal enterprise processes are unorganized
Very few organizations are at Level 0, the level set for definitional purposes in the maturity model.
Level 1
initial or temporary level
Generic data management using a limited toolset with little or no governance activity
Data processing is highly dependent on a small number of experts, with roles and responsibilities defined separately across departments
Solutions for managing data are limited
Data quality issues are prevalent but cannot be resolved, infrastructure support is at the business unit level
level 2
repeatable level
Have consistent tools and role definitions to support process execution
Organizations are beginning to use centralized tools and provide more monitoring means for data management
Role definitions and processes are not entirely tied to specific experts
The organization becomes aware of data quality issues and concepts and begins to recognize the concepts of master data and reference data
Level 3
level defined
Level 3 will introduce and institutionalize scalable data management processes and view data management as an organizational enabler
Characteristics include controlled data replication within the organization, generally improved overall data quality, and consistent policy definition and management
A more formal process definition can significantly reduce manual intervention, which means that with a centralized design process, the results of the process are more predictable.
Evaluation criteria may include development of data management policies, use of scalable processes, and consistency of data models and system controls
level 4
Already managed
The accumulation of experience gained from Level 1 to Level 3 growth enables organizations to predict outcomes as they approach new projects and tasks and begin to manage data-related risks. Data management includes a number of performance indicators.
Characteristics of Level 4 include standardization of data management tools from desktop to infrastructure, and well-structured centralized planning and governance capabilities
Level 5
Optimization level
When data management practices are optimized, they are highly predictable due to process automation and technical change management, and organizations at this maturity level are more focused on continuous improvement.
At level 5, tools enable viewing data across processes
Control data proliferation to prevent unnecessary duplication, and use easy-to-understand metrics to manage and measure data quality and processes
Evaluation Criteria
Each competency level has specific assessment criteria related to the process being assessed
At any level, the evaluation criteria will be evaluated according to a scale such as 1-not started, 2-in progress, 3-available, 4-effective, to show the progress of that level and move towards the next level.
Existing DAMA framework
CMMI data management maturity model
EDM Committee DCAM
IBM Data Governance Council Maturity Model
Stanford Data Governance Maturity Model
Cartner’s Enterprise Information Management Maturity Model
Activity
Data management maturity assessment requires planning
The purpose of assessment is to uncover current strengths and opportunities for improvement, not to solve problems
Planning assessment activities
Define goals
Select frame
Define organizational scope
Define interaction
plan communication
Perform a maturity assessment
collect information
Perform assessment
Interpret results and recommendations
Interpretation of results includes identifying opportunities for advancement consistent with organizational strategy and recommending actions to capitalize on these opportunities
Report assessment results
Business drivers for assessment
Overall results of the assessment
Ratings with gaps by topic
Suggested ways to bridge the gap
Observed Organizational Strengths
risk of progression
Investment and Outcome Options
Governance and metrics to measure progress
Resource Analysis and Potential Future Utility
Develop management briefings
The Assessment Manager prepares a management briefing summarizing the findings (including strengths, gaps, recommendations) that management uses as input in making decisions regarding goals, plans, and timelines.
Develop targeted improvement plans
Reassess maturity
Re-evaluations should be carried out regularly as part of a cycle of continuous improvement
Establish a baseline rating with the first assessment
Define reassessment parameters, including organization scope
Repeat DMM assessment on published schedule as needed
Track trends relative to an initial baseline
Develop recommendations based on reassessment results
Reassessment can also reinvigorate or refocus your efforts
Measurable progress helps maintain buy-in and enthusiasm across the organization
Changes in regulatory frameworks, changes in internal and external policies, governance approaches and strategic innovations are other reasons for periodic reassessment
tool
Data Management Maturity Framework
communication plan
Collaboration tools
Knowledge management and metadata repository
method
Choose DMM framework
standard
Ease of use
Comprehensiveness
Scalability and flexibility
Built-in future evolution path
Industry Agnostic Domain Industry Specific Theory
level of abstraction or detail
non-prescriptive
Organized by topic
Repeatable
Backed by a neutral, independent organization
technology neutral
Training support
DAMA-DMBOK framework usage
Implementation Guide
Readiness Assessment/Risk Assessment
Organizational and cultural change
maturity management governance
DAMA process supervision
Metrics
DMMA rating
Resource utilization
risk exposure
Spend management
DMMA input
speed of change