Data management

What you will study

This module takes a practice-based approach based on an organisation you are familiar with. It gives you the fundamental knowledge and understanding of the data management principles, practices and technologies required to develop policies, procedures and systems that control, protect, deliver and enhance the value of the organisation’s data asset.

You will also have an opportunity to investigate emerging trends in data management and acquire the personal development skills you need to keep abreast of important developments in a rapidly expanding field. In addition, researching information about data management from various sources will give you critical evaluation skills and the ability to write about different approaches to this subject.

The module also covers the following Knowledge Areas (DMBOK2), which describe the scope and context of data management activities: 

• Data Governance, which provides direction and oversight for data management by establishing a system of decision rights over data that accounts for the needs of the enterprise.
• Data Architecture, which defines the blueprint for managing data assets by aligning with organizational strategy to establish strategic data requirements and designs to meet these requirements.
• Data Modelling and Design, which is the process of discovering, analysing, representing, and communicating data requirements in a precise form called the data model.
• Data Storage and Operations, which includes the design, implementation, and support of stored data to maximize its value. Operations provide support throughout the data lifecycle from planning for to disposal of data.
• Data Security, which ensures that data privacy and confidentiality are maintained, that data is not breached, and that data is accessed appropriately.
• Data Integration and Interoperability, which includes processes related to the movement and consolidation of data within and between data stores, applications, and organizations.
• Document and Content Management, which 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, which includes ongoing reconciliation and maintenance of core critical shared data to enable consistent use across systems of the most accurate, timely, and relevant version of truth about essential business entities.
• Data Warehousing and Business Intelligence, which includes the planning, implementation, and control processes to manage decision support data and to enable knowledge workers to get value from data via analysis and reporting.
• Metadata, which 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, which includes the planning and implementation of quality management techniques to measure, assess, and improve the fitness of data for use within an organization.

In addition to the above Knowledge Areas, the module also covers the following topics:

• Data Handling Ethics, which 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, which describes the technologies and business processes that emerge as our ability to collect and analyse large and diverse data sets increases.
• Data Management Maturity Assessment, which outlines an approach to evaluating and improving an organization’s data management capabilities. 
• Data Management Organization and Role Expectations, which provide best practices and considerations for organizing data management teams and enabling successful data management practices.
• Data Management and Organizational Change Management, which describes how to plan for and successfully move through the cultural changes that are necessary to embed effective data management practices within an organization.

In the module assessment you will have an opportunity to engage with an organisational problem of your choice, working towards fit-for-purpose data management policies, procedures and systems. You will also have an opportunity to carry out some independent research into issues in data management, including analysing, evaluating and presenting results.

The book DAMA-DMBOK: Data Management Body of Knowledge (2nd edition) is to be provided electronically via the module website. All other module material is delivered online and makes extensive use of a range of media and resources to support your learning.

Teaching and assessment

Support from your tutor

You will have a tutor who will be responsible for monitoring your progress on the module, marking and commenting on your written work and whom you can contact for advice and guidance.

Contact us if you want to know more about study with The Open University before you register.

Assessment

The assessment details for this module can be found in the facts box above.

You must use the online eTMA system to submit your tutor-marked assignments (TMAs) and your end-of-module assessment (EMA).

Professional recognition

Application for recognition will be made to BCS, The Chartered Institute for IT for exemption from some of its membership requirements for holders of an appropriate MSc in Computing.