Data Governance
Overview
Data governance refers to the overall management of the availability, usability, integrity, and security of the data employed in an enterprise. It is a set of processes, roles, policies, standards, and metrics that ensure the effective and efficient use of information in enabling an organization to achieve its goals. This includes such areas as data quality, data management, data policies, business process management, and risk management surrounding the handling of data in an enterprise.
Importance of Data Governance
Data governance is crucial for organizations for several reasons. It ensures that data is consistent and trustworthy, which is essential for all types of reporting, business intelligence, and data analytics. It also helps to ensure regulatory compliance, as many regulations today require reporting with the assurance that the data is correct. Moreover, data governance helps to improve the availability, usability, integrity, and security of data, which can lead to improved decision-making within the organization.
Data Governance Framework
A data governance framework refers to the process of building a model for managing data across an organization. It involves the development of processes, policies, standards, and metrics for data management. This framework is typically developed by a data governance council or committee, which includes representatives from all areas of the organization. The framework is then implemented and enforced by data stewards, who are responsible for ensuring that the data is managed according to the established policies and standards.
Data Governance Council
The data governance council, also known as a data governance committee, is a group of individuals who are responsible for the strategic direction and oversight of data governance initiatives within an organization. This council typically includes representatives from all areas of the organization, including business operations, IT, legal, and compliance. The council is responsible for developing the data governance framework, establishing data policies and standards, and overseeing the implementation and enforcement of these policies and standards.
Data Stewardship
Data stewardship refers to the management and oversight of an organization's data assets to ensure that they are optimally used and protected. Data stewards are individuals who are responsible for ensuring that the data is managed according to the established data governance policies and standards. They play a crucial role in data governance initiatives by ensuring that the data is accurate, reliable, and secure. Data stewards also work closely with the data governance council to implement and enforce the data governance framework.
Data Quality
Data quality refers to the condition of a set of values of qualitative or quantitative variables. It is an essential aspect of data governance, as high-quality data is necessary for accurate reporting, business intelligence, and data analytics. Data quality is typically measured and monitored using a variety of techniques, including data profiling, data cleansing, and data auditing. Data governance policies and standards often include provisions for ensuring data quality.
Data Management
Data management involves the development and execution of architectures, policies, practices, and procedures in order to manage the information lifecycle needs of an organization. It is a key component of data governance, as it involves the physical and logical management of data, including data architecture, data modeling, data warehousing, and database management.
Data Policies
Data policies are the rules and guidelines that govern the collection, use, storage, and dissemination of data in an organization. These policies are typically developed by the data governance council and enforced by data stewards. They cover a wide range of issues, including data quality, data privacy, data security, and data lifecycle management.
Business Process Management
Business process management (BPM) is a discipline that uses various methods to discover, model, analyze, measure, improve, and optimize business processes. BPM involves the management of both automated and non-automated processes to achieve consistent, targeted results aligned with an organization's strategic goals. BPM is closely related to data governance, as it involves the management of processes that use and generate data.
Risk Management
Risk management is the identification, evaluation, and prioritization of risks followed by coordinated and economical application of resources to minimize, monitor, and control the probability or impact of unfortunate events. In the context of data governance, risk management involves identifying and managing the risks associated with data, including data breaches, data corruption, and data loss.
Regulatory Compliance
Regulatory compliance refers to an organization's adherence to laws, regulations, guidelines, and specifications relevant to its business processes. In the context of data governance, regulatory compliance involves ensuring that the organization's data management practices are in compliance with relevant data protection and privacy laws and regulations.