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Data governance is a term used on both a macro and a micro level. The former is a political concept and forms part of international relations and Internet governance; the latter is a data management concept and forms part of corporate data governance.
Data governance at the macro level involves regulating cross-border data flows among countries, which is more precisely termed international data governance. This field formed in the early 2000s [1] and consists of "norms, principles and rules governing various types of data." [2]
There have been several international groups established by research organizations that aim to grant access to their data. These groups that enable an exchange of data are, as a result, exposed to domestic and international legal interpretations that ultimately decide how data is used. However, as of 2023, there are no international laws or agreements specifically focused on data protection. [3]
Here the focus is on an individual company. Here data governance is a data management concept concerning the capability that enables an organization to ensure that high data quality exists throughout the complete lifecycle of the data, and data controls are implemented that support business objectives. The key focus areas of data governance include availability, usability, consistency, data integrity and security, and standards compliance. The practice also includes establishing processes to ensure effective data management throughout the enterprise, such as accountability for the adverse effects of poor data quality, and ensuring that the data which an enterprise has can be utilized by the entire organization.
A data steward is a role that ensures that data governance processes are followed and that guidelines are enforced, and recommends improvements to data governance processes.
Data governance involves the coordination of people, processes, and information technology necessary to ensure consistent and proper management of an organization's data across the business enterprise. It provides all data management practices with the necessary foundation, strategy, and structure needed to ensure that data is managed as an asset and transformed into meaningful information. Goals may be defined at all levels of the enterprise and doing so may aid in acceptance of processes by those who will use them. Some goals include:
These goals are realized by the implementation of data governance programs, or initiatives using change management techniques.
When companies seek to take charge of their data, whether by choice or necessity, they empower their employees, establish processes, and utilize technology to accomplish this objective. [5]
While data governance initiatives can be driven by a desire to improve data quality, they are often driven by C-level leaders responding to external regulations. In a recent report conducted by CIO WaterCooler community, 54% stated the key driver was efficiencies in processes; 39% - regulatory requirements; and only 7% customer service. [6] Examples of these regulations include Sarbanes–Oxley Act, Basel I, Basel II, HIPAA, GDPR, cGMP, [7] and a number of data privacy regulations. To achieve compliance with these regulations, business processes and controls require formal management processes to govern the data subject to these regulations. [8] Successful programs identify drivers meaningful to both supervisory and executive leadership.
Common themes among the external regulations center on the need to manage risk. The risks can be financial misstatement, inadvertent release of sensitive data, or poor data quality for key decisions. Methods to manage these risks vary from industry to industry. Examples of commonly referenced best practices and guidelines include COBIT, ISO/IEC 38500, and others. The proliferation of regulations and standards creates challenges for data governance professionals, particularly when multiple regulations overlap the data being managed. Organizations often launch data governance initiatives to address these challenges.
Data governance initiatives improve quality of data by assigning a team responsible for data's accuracy, completeness, consistency, timeliness, validity, and uniqueness. [9] This team usually consists of executive leadership, project management, line-of-business managers, and data stewards. The team usually employs some form of methodology for tracking and improving enterprise data, such as Six Sigma, and tools for data mapping, profiling, cleansing, and monitoring data.
Data governance initiatives may be aimed at achieving a number of objectives including offering better visibility to internal and external customers (such as supply chain management), compliance with regulatory law, improving operations after rapid company growth or corporate mergers, or to aid the efficiency of enterprise knowledge workers by reducing confusion and error and increasing their scope of knowledge.[ citation needed ] Many data governance initiatives are also inspired by past attempts to fix information quality at the departmental level, leading to incongruent and redundant data quality processes. Most large companies have many applications and databases that can not easily share information. Therefore, knowledge workers within large organizations often do not have access to the data they need to best do their jobs. When they do have access to the data, the data quality may be poor. By setting up a data governance practice or corporate data authority (individual or area responsible for determining how to proceed, in the best interest of the business, when a data issue arises), these problems can be mitigated.
Implementation of a data governance initiative may vary in scope as well as origin. Sometimes, an executive mandate will arise to initiate an enterprise wide effort. Sometimes the mandate will be to create a pilot project or projects, limited in scope and objectives, aimed at either resolving existing issues or demonstrating value. Sometimes an initiative will originate lower down in the organization’s hierarchy and will be deployed in a limited scope to demonstrate value to potential sponsors higher up in the organization. The initial scope of an implementation can vary greatly as well, from review of a one-off IT system, to a cross-organization initiative.
Leaders of successful data governance programs declared at the Data Governance Conference in Orlando, FL, in December 2006 that data governance is about 80 to 95 percent communication. [10] That stated, it is a given that many of the objectives of a data governance program must be accomplished with appropriate tools. Many vendors are now positioning their products as data governance tools. Due to the different focus areas of various data governance initiatives, a given tool may or may not be appropriate. Additionally, many tools that are not marketed as governance tools address governance needs and demands.
A document management system (DMS) is usually a computerized system used to store, share, track and manage files or documents. Some systems include history tracking where a log of the various versions created and modified by different users is recorded. The term has some overlap with the concepts of content management systems. It is often viewed as a component of enterprise content management (ECM) systems and related to digital asset management, document imaging, workflow systems and records management systems.
Information technology (IT)governance is a subset discipline of corporate governance, focused on information technology (IT) and its performance and risk management. The interest in IT governance is due to the ongoing need within organizations to focus value creation efforts on an organization's strategic objectives and to better manage the performance of those responsible for creating this value in the best interest of all stakeholders. It has evolved from The Principles of Scientific Management, Total Quality Management and ISO 9001 Quality Management System.
Information technology service management (ITSM) are the activities performed by an organization to design, build, deliver, operate and control IT services offered to customers.
In general, compliance means conforming to a rule, such as a specification, policy, standard or law. Compliance has traditionally been explained by reference to deterrence theory, according to which punishing a behavior will decrease the violations both by the wrongdoer and by others. This view has been supported by economic theory, which has framed punishment in terms of costs and has explained compliance in terms of a cost-benefit equilibrium. However, psychological research on motivation provides an alternative view: granting rewards or imposing fines for a certain behavior is a form of extrinsic motivation that weakens intrinsic motivation and ultimately undermines compliance.
Data quality refers to the state of qualitative or quantitative pieces of information. There are many definitions of data quality, but data is generally considered high quality if it is "fit for [its] intended uses in operations, decision making and planning". Moreover, data is deemed of high quality if it correctly represents the real-world construct to which it refers. Furthermore, apart from these definitions, as the number of data sources increases, the question of internal data consistency becomes significant, regardless of fitness for use for any particular external purpose. People's views on data quality can often be in disagreement, even when discussing the same set of data used for the same purpose. When this is the case, data governance is used to form agreed upon definitions and standards for data quality. In such cases, data cleansing, including standardization, may be required in order to ensure data quality.
COBIT is a framework created by ISACA for information technology (IT) management and IT governance.
Information technology controls are specific activities performed by persons or systems to ensure that computer systems operate in a way that minimises risk. They are a subset of an organisation's internal control. IT control objectives typically relate to assuring the confidentiality, integrity, and availability of data and the overall management of the IT function. IT controls are often described in two categories: IT general controls (ITGC) and IT application controls. ITGC includes controls over the hardware, system software, operational processes, access to programs and data, program development and program changes. IT application controls refer to controls to ensure the integrity of the information processed by the IT environment. Information technology controls have been given increased prominence in corporations listed in the United States by the Sarbanes-Oxley Act. The COBIT Framework is a widely used framework promulgated by the IT Governance Institute, which defines a variety of ITGC and application control objectives and recommended evaluation approaches.
The chief risk officer (CRO), chief risk management officer (CRMO), or chief risk and compliance officer (CRCO) of a firm or corporation is the executive accountable for enabling the efficient and effective governance of significant risks, and related opportunities, to a business and its various segments. Risks are commonly categorized as strategic, reputational, operational, financial, or compliance-related. CROs are accountable to the Executive Committee and The Board for enabling the business to balance risk and reward. In more complex organizations, they are generally responsible for coordinating the organization's Enterprise Risk Management (ERM) approach. The CRO is responsible for assessing and mitigating significant competitive, regulatory, and technological threats to a firm's capital and earnings. The CRO roles and responsibilities vary depending on the size of the organization and industry. The CRO works to ensure that the firm is compliant with government regulations, such as Sarbanes–Oxley, and reviews factors that could negatively affect investments. Typically, the CRO is responsible for the firm's risk management operations, including managing, identifying, evaluating, reporting and overseeing the firm's risks externally and internally to the organization and works diligently with senior management such as chief executive officer and chief financial officer.
Enterprise risk management (ERM) in business includes the methods and processes used by organizations to manage risks and seize opportunities related to the achievement of their objectives. ERM provides a framework for risk management, which typically involves identifying particular events or circumstances relevant to the organization's objectives, assessing them in terms of likelihood and magnitude of impact, determining a response strategy, and monitoring process. By identifying and proactively addressing risks and opportunities, business enterprises protect and create value for their stakeholders, including owners, employees, customers, regulators, and society overall.
Internal auditing is an independent, objective assurance and consulting activity designed to add value and improve an organization's operations. It helps an organization accomplish its objectives by bringing a systematic, disciplined approach to evaluate and improve the effectiveness of risk management, control and governance processes. Internal auditing might achieve this goal by providing insight and recommendations based on analyses and assessments of data and business processes. With commitment to integrity and accountability, internal auditing provides value to governing bodies and senior management as an objective source of independent advice. Professionals called internal auditors are employed by organizations to perform the internal auditing activity.
Governance, risk management and compliance (GRC) is the term covering an organization's approach across these three practices: governance, risk management, and compliance.
SOA Governance is a set of processes used for activities related to exercising control over services in a service-oriented architecture (SOA). One viewpoint, from IBM and others, is that SOA governance is an extension (subset) of IT governance which itself is an extension of corporate governance. The implicit assumption in this view is that services created using SOA are just one more type of IT asset in need of governance, with the corollary that SOA governance does not apply to IT assets that are "not SOA". A contrasting viewpoint, expressed by blogger Dave Oliver and others, is that service orientation provides a broad organising principle for all aspects of IT in an organisation — including IT governance. Hence SOA governance is nothing but IT governance informed by SOA principles.
Continuous monitoring is the process and technology used to detect compliance and risk issues associated with an organization's financial and operational environment. The financial and operational environment consists of people, processes, and systems working together to support efficient and effective operations. Controls are put in place to address risks within these components. Through continuous monitoring of the operations and controls, weak or poorly designed or implemented controls can be corrected or replaced – thus enhancing the organization's operational risk profile. Investors, governments, the public, and other stakeholders continue to increase their demands for more effective corporate governance and business transparency.
Information security management (ISM) defines and manages controls that an organization needs to implement to ensure that it is sensibly protecting the confidentiality, availability, and integrity of assets from threats and vulnerabilities. The core of ISM includes information risk management, a process that involves the assessment of the risks an organization must deal with in the management and protection of assets, as well as the dissemination of the risks to all appropriate stakeholders. This requires proper asset identification and valuation steps, including evaluating the value of confidentiality, integrity, availability, and replacement of assets. As part of information security management, an organization may implement an information security management system and other best practices found in the ISO/IEC 27001, ISO/IEC 27002, and ISO/IEC 27035 standards on information security.
Master data management (MDM) is a discipline in which business and information technology collaborate to ensure the uniformity, accuracy, stewardship, semantic consistency, and accountability of the enterprise's official shared master data assets.
Information technology risk, IT risk, IT-related risk, or cyber risk is any risk relating to information technology. While information has long been appreciated as a valuable and important asset, the rise of the knowledge economy and the Digital Revolution has led to organizations becoming increasingly dependent on information, information processing and especially IT. Various events or incidents that compromise IT in some way can therefore cause adverse impacts on the organization's business processes or mission, ranging from inconsequential to catastrophic in scale.
Security level management (SLM) comprises a quality assurance system for information system security.
In organizations, shadow IT refers to information technology (IT) systems deployed by departments other than the central IT department, to bypass limitations and restrictions that have been imposed by central information systems. While it can promote innovation and productivity, shadow IT introduces security risks and compliance concerns, especially when such systems are not aligned with corporate governance.
Information governance, or IG, is the overall strategy for information at an organization. Information governance balances the risk that information presents with the value that information provides. Information governance helps with legal compliance, operational transparency, and reducing expenditures associated with legal discovery. An organization can establish a consistent and logical framework for employees to handle data through their information governance policies and procedures. These policies guide proper behavior regarding how organizations and their employees handle information whether it is physically or electronically.
The NIST Cybersecurity Framework (CSF) is a set of voluntary guidelines designed to help organizations assess and improve their ability to prevent, detect, and respond to cybersecurity risks. Developed by the U.S. National Institute of Standards and Technology (NIST), the framework was initially published in 2014 for critical infrastructure sectors but has since been widely adopted across various industries, including government and private enterprises globally. The framework integrates existing standards, guidelines, and best practices to provide a structured approach to cybersecurity risk management.
At the inaugural Data Governance Conference in Orlando, Florida, in December 2006, leaders of successful data governance programs declared that in their experience, data governance is between 80 and 95 percent communication. Clearly, data governance is not a typical IT project.
