Core Functions and Disciplines of Data Management
Data Governance – Oversight of Data Management
Data Governance is the core component of Data Management, which handles direction and oversight for Data Management.
Data Architecture – Framework of Data Strategy
Data Architecture is a framework and foundation of Data Strategy. Data Architecture, the blueprint shows how data is acquired, transported, stored, queried, and secured.
Data Modeling and Design – Creating the Data Blueprint
Data Modeling and Design is the process and software engineering to gather, analyze, represent and communicate data requirements in a model form, called Data Model.
Data Storage and Operations – Managing and Supporting Data Value
Data Storage and Operations is defined as designing, Implementing, and Supporting Data to maximize its Value.
Data Security – Safeguarding Data Access and Privacy
Data Security ensures that Data is accessed appropriately and maintains its privacy & confidentiality.
Data Integration and Interoperability – Consolidating Data Across Systems
Data Integration and Interoperability includes policies, procedures, and processes related to the Data Movement and Consolidation within and between data stores, applications, and organizations.
Document and Content Management – Lifecycle of Unstructured Data
Document and Content Management includes planning, implementation, and control activities used to manage the lifecycle of data and information found in a range of unstructured media, especially documents needed to support legal and regulatory compliance requirements.
Reference and Master Data – Maintaining Core Shared Data
Reference and Master Data includes ongoing maintenance of core critical shared data to enable
consistent use across systems of the most accurate, timely, and relevant version of the truth.
Data Warehousing and Business Intelligence – Enabling Decision Support
Data Warehousing and Business Intelligence includes the planning, implementation, and control processes to manage decision support data and enable knowledge workers to get value from data via analysis and reporting.
Metadata – Managing Data About Data Management – Key Components
Metadata includes planning, implementation, and control activities to enable access to high-quality, integrated Metadata, including definitions, models, data flows, and other information critical to understanding data and the systems through which it is created, maintained, and accessed.
Data Quality – Measuring and Improving Data Fitness
Data Quality includes the planning and implementation of quality management techniques to measure, assess, and improve the fitness of data for use within an organization.
Data Handling Ethics – Ethical Use of Data Management – Key Components
Data Handling Ethics describes the central role that data ethics plays in making informed, socially responsible decisions about data and its uses. Awareness of the ethics of data collection, analysis, and use should guide all data management professionals.
Big Data and Data Science – Advanced Analytics and Technologies
Big Data and Data Science describe the technologies and business processes that emerge as our ability to collect and analyze large and diverse data sets increases.
Data Management Maturity Assessment – Evaluating Capabilities
Data Management Maturity Assessment outlines an approach to evaluating and improving an organization’s data management capabilities.
Data Management Roles and Responsibilities – Organizing for Success
Data Management Organization and Role Expectations provide best practices and considerations for organizing data management teams and enabling successful data management practices.
Organizational Change and Data Management – Driving Cultural Adoption
Data Management and Organizational Change Management describes how to plan for and successfully move through the cultural changes that are necessary to embed effective data management practices within an organization.
