Data Management Maturity Model. Overview

Transcription

1 Data Management Maturity Model Overview UPMC Center of Excellence Pittsburgh Jul 29, 2013

2 Data Management Maturity Model - Background A broad framework encompassing foundational data management capabilities, a measure for organizations to evaluate capability maturity and identify gaps, incorporating guidelines for improvements Joint initiative of the CMMI Institute and the Enterprise Data Management Council, with selected corporate sponsors Content model was independently developed by a consortium of experts over 18 months; now being transformed and formalized to align closely with CMMI, with a target release Jan 2014 A full suite of courses are in development, leading to certification and licensing of DMM Appraisers across all industries Citibank first piloted the DMM framework across 22 of its organizations DMM Assessments have been conducted for Microsoft Corporation, the Securities and Exchange Commission, the Depository Trust Clearing Corporation, and the Office of Financial Research.

3 DMM at a Glance 6 Sections, 25 Process Areas Purpose Introduction - Goals Questions - Capability Level Criteria Work Products Policies Processes Standards Governance Metrics Enabling Technology Scores each component for capability level 1 to 5 Data Management Strategy Data Governance Data Quality Platform & Architecture Data Operations Supporting Processes

4 DMM Assessment Method DMM can be used as a standalone guide to successive achievements in data management processes, however - Greatest value is gained by evaluating capabilities as a collaborative effort involving a broad range of stakeholders Workshop approach, consensus affirmations and artifact (evidence) review Scoring, Findings, Observations, Next Steps Our conference DMM discussion sessions are a sample of this approach Enhanced rigor will be introduced to serve as an externally auditable record of maturity, similar to CMMI SCAMPI A.

5 Sample - Data Management Maturity Summary

6 Data Management Strategy Name Data Management Strategy Data Management Strategy Communications Data Management Function Business Case Data Management Funding Description Goals, objectives, principles, business value, prioritization, metrics, and sequence plan for the data management program Communications strategy for data management initiatives and mechanisms to ensure business, IT, and data management stakeholders are aligned with bi-directional feedback Structure of data management organization, responsibilities and accountability, interaction model, staffing for data management resources, executive oversight Decision rationale for determining what data management initiatives should be funded based on benefits to the organization and financial considerations Funding justification for the data management program and initiatives, operational and financial metrics

7 Data Governance Data Governance Governance Management Business Glossary Metadata Management Structure of data governance, governance processes and leadership, metrics development and monitoring Creation, change management, and compliance for terms, definitions, and properties Strategy, classification, capture, integration, and accessibility of business, technical, process, and operational metadata

8 Data Quality Data Quality Data Quality Strategy Data Profiling Data Quality Assessment Data Cleansing Plan and initiatives for the data quality program, aligned with business objectives and impacts Analysis of semantic data content in physical data stores for meaning and defect detection Assessment and improvement of data quality, business rules and known issues analysis, measuring impact and costs Mechanisms to clean data, reporting and tracking of data issues for correction with impact and cost analysis

9 Platform & Architecture Platform & Architecture Architectural Approach Architectural Standards Data Management Platform Data Integration Historical Data, Archiving and Retention Architectural strategy, frameworks, and standards for implementation planning Data standards for representation, access, and distribution Technology and capability platforms selection for data distribution and integration into consuming applications Integration and reconciliation of data from multiple sources into target destinations, standards and best practices, data quality processes at point of entry Management of historical data, archiving, and retention requirements

10 Data Operations Data Operations Data Requirements Definition Data Lifecycle Provider Management Process and standards for developing, prioritizing, evaluating, and validating data requirements Mapping of data to business processes as data flows from one process to another Standardization of data sourcing process, SLAs, and management of data provisioning from internal and external sources

11 Supporting Processes Supporting Processes Measurement and Analysis Process Management Process Quality Assurance Risk Management Configuration Management Adapted from CMMI Establishing and reporting metrics and statistics for each process area within the data management program, supports managing to performance milestones Management and enforcement of policies, processes, and standards, from creation to dissemination to sunsetting Evaluation and audit to ensure quality execution in all data management process areas Identifying, categorizing, managing and mitigating business and technical risks for the data management program Establishing and maintaining the integrity of data management artifacts and products, and management of releases

12 Supporting Information Standards & Procedures Standards and Procedures Shared Services Utilization Quality Control Data Access Distribution On-Boarding Redistribution Entitlement and Permissioning Sensitive Data Audit and Compliance Data Precedence / Business Rules Data Transformation Business Data Continuity Addendum to DMM These topics were developed and represented in a lifecycle fashion, with four phases: Defined, Developed, Verified, and Approved, specifying business and technical roles and key artifacts produced by the process. Some topics may be promoted to DMM Process Areas in a future release.