Data Management is a comprehensive collection of practices, concepts, and processes dedicated to leveraging data assets for business success and compliance with data regulations. It spans the entire lifecycle of a given data asset from its original creation point to its final retirement, from end to end of an enterprise.
The practice includes an extensive list of associated and related topics, including:
- Data Governance
- Data Architecture Management
- Data Development (Including Big Data)
- Database Operations Management (including Database Management)
- Data Security Management
- Master Data Management and Reference Data
- Data Warehousing and Business Intelligence (BI) Management
- Document and Content Management
- Metadata Management
- Data Quality Management
According to the Data Management Body of Knowledge (DMBOK), a Data Management professional is:
“Any person who works in any facet of data management [and] fills numerous roles, from the highly technical (e.g., database administrators, network administrators, programmers) to the strategic business (e.g., Data Stewards, Data Strategists, Chief Data Officers).”
Businesses Practice Data Management to:
- Handle exponential data growth.
- Improve customer relationships.
- Eliminate silos of information.
- Make data assets available for business use.
- Get a better return on investment (ROI).
- Deliver products and services on-demand.
- Achieve digital transformation.
Other Definitions Include:
- “The development, execution, and supervision of plans, policies, programs, and practices that deliver, control, protect, and enhance the value of data and information assets throughout their lifecycles.” (DAMA-DMBoK)
- “The practices, architectural techniques, and tools for achieving consistent access to and delivery of data across the spectrum of data subject areas and data structure types in the enterprise, to meet the data consumption requirements of all applications and business processes.” (Gartner Glossary)
- The work ensuring “that an organization’s entire body of data is accurate, consistent, readily accessible, and properly secured.” (TechRepublic)
- “A framework that clarifies the primary purpose of an organization and guides it to apply a data strategy.” (Harvard Business Review).
- Improved operations management
- More effective marketing and sales
- Better regulation and compliance controls
- Enhanced security and privacy
- Reduction of risk across the board
- Faster application and system development
- Improved decision-making and reporting
- Sustained business growth
- Business and technical alignment
- Streamlined operations
- Greater collaboration and revenue growth
- More consistency across all enterprise processes
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