Data Governance: Planning, oversight, and control over management of data and the use of data and data-related resources.

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Data Architecture: Defining the data needs of the enterprise and designing the master blueprints to meet those needs including development and maintenance of an enterprise data framework and its connection with application solutions and enterprise architecture

 

Data Modeling & Design: Analysis, design, building, testing, and maintenance of solutions to meet the data needs of the enterprise.

 

Data Storage & Operations: Planning, control and support for structured data assets across the data life cycle, from creation and acquisition through archiving.

Data Security: Planning, development and execution of security policies and procedures to provide proper authentication, authorization, access and auditing of data and information. This includes privacy, confidentiality and appropriate access of data.

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Data Integration & Interoperability: Acquisition, extraction, transformation, movement, delivery, replication, federation, virtualization and operational

 

Documents & Content: Storing, protecting, indexing, and enabling access to data found in unstructured sources (electronic files and physical records), and making this data available for integration and interoperability with structured (database) data.

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Reference & Master Data: Managing shared data to reduce redundancy and ensure better data quality through standardized definition and use of data values. Enables consistency with a “golden version” of contextual data values. (Trusted / authoritative sources of shared data and domain values.)

 

Data Warehousing & Business Intelligence: Managing analytical data processing and enabling access to decision support data for reporting and analysis

Metadata: Collecting, categorizing, maintaining, integrating, controlling, managing, and delivering metadata (data about data).

 

Data Quality: Measure, assess, improve, monitor and ensure the fitness of data for use.