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Data Quality Project - Coggle Diagram
Data Quality Project
(3) WHAT:
Data Profiling
Outlier detection
Profile execution and scheduling
Profile performance tuning
Data Cleansing
Data Quality Rules
Rules used to identifying anormalies
Rules used to fix the anomalies
Rules to manage and categorize anomalies
Reusable objects and widgets
Data Enrichment
Identify reference data
Create data dictionaries/use existing
Reference data maintainance
Data Pipelies
Design data delivery processes
Design DQ exceptions feedback loops
Data monitoring
Reports and Dash
Alerts and communication
Automate creation of tickets/cases
(2) HOW:
People
CDW Team
Client Director
Senior Solutions Architect
Tech Consultants
Functional/Non-Tech Consultants
QA Analysts
Project Manager
Client Team
Exec. Sponsor
Data Governance Leader
Data Engineering Leader
Technical SME's
Business SME's
Data Stewarts/Custodians
Other stakeholders
Process
Identify the excpected business outcomes and objectives
Define roles and responsibilities
Priotize and rank the project/pursuits/issues
Establish best practices
Define DQ policies, standardized practices and procedures
Define the workflows e.g.
Normal workflow
Exception workflow
External communications workflow (third-party)
Define DQ metrics and KPI's
DQ dimensions
Threasholds: Good, Bad, Acceptable
Identify universal needs e.g.
Address Verification
Phone and Email verification
National change of address
Reference datasets
DQ reports and dashboards
Technology
Catalog the existing adjacent technology solutions
Determine current capabilities and gaps
Current architecture and data flows
Design of the future architecture including DQ capabilities
Evaluation and selection technology solution
Implemntation of technology solution
(1) WHY:
Outcomes
Improved business decision making
Prevent regulatory compliance failures
Improve operational efficiency
Opportunity
CDO recognizes the size of the DQ challenges
Complexity of the landscape and architecture
Limited capacity of the team (small team)
Lack of experience and depth
Must align with overall corporate Data Governance strategy
4 ACTION ITEMS:
DQ Workshop Proposal
Technology evaluation proposal