Data Governance: objectives, principles and good practices for data management
Data governance is a set of processes, policies, standards and metrics focused on ensure the quality, availability, integrity and security of data in an organization.
The main objective of this discipline is to ensure that data is managed effectively and responsibly.
Also search for:
- improve quality and fidelity,
- comply with existing regulations,
- minimize the risks,
- maximize business value.
In this article we analyze the great importance of data governance for organizations, the aspects to consider in data management, the main regulations in force and the key role of the Data Protection Officer.
Data governance market news
The global data governance market size was valued at $3.66 billion in 2023.
Growth of $4.44 billion is projected for 2024, and a progression to 19.86 billion dollars in 2032.
The information comes from the market report of Fortune Business Insights, which estimates a CAGR of 20.6% for the period 2024-2032.
The study highlights that data management has become a essential aspect in the digital world. It is also noted that organizations are promoting projects for extract the maximum value from the data they collect, to make better decisions.
In this sense, it is interesting to highlight that the main benefit received by companies that develop Data Governance programs is the Improving data quality and confidence.
According to the study, the volume of data is expected to reach 180 zettabytes by 2025, three times more than that generated in 2020.
Furthermore, the increasing presence of people online, the extensive use of social media platforms and the expansion of mobile devices that have contributed to the increase in data, result in massive data flows.
In response to this phenomenon, companies are looking Advanced governance solutions to manage and analyze this information safely and efficiently.
Universal objectives and principles of data governance
For the Data Governance Institute, the typical universal objectives of a data governance program are as follows:
- Enable better decision making.
- Reduce operational friction.
- Protecting the needs of data stakeholders.
- Train management and staff to adopt common approaches to data problems.
- Create standard and repeatable processes.
- Reduce costs and increase effectiveness by coordinating efforts.
- Ensure transparency of processes.
According to the institution, all successful data management and governance programs, processes and projects share these eight guiding principles of data governance:
- Integrity in the relationships of those involved in the process.
- Transparency in data governance and management processes.
- Auditability of decisions, processes and controls.
- Responsibility for cross-functional decisions, processes and controls.
- Stewardship (management responsibilities).
- Checks and balances between business and technology teams, and between those who create, collect and manage information, and between those who use it and the people who introduce standards and compliance requirements.
- Standardization of business data.
- Change management for reference data values and the structure and use of master data and metadata.
What is the importance of data governance?
Data governance is essential for ensure that data is treated as a valuable asset. Also to maximize its usefulness and protection in an organization.
Its importance lies in several reasons, linked to the following possibilities:
- Ensure data quality, accuracy, completeness and consistency to increase confidence in decision-making.
- Ensure the protection of sensitive and critical data of the organization, its clients and suppliers, against internal and external threats, such as cyber attacks or leaks.
- Facilitate timely access to the right data by people with the right permissions, to improve operational efficiency and productivity
- Define and manage the complete life cycle of data, from creation to deletion, optimizing its use and storage.
- Provide a solid foundation of reliable data to support strategic and operational decision-making.
What benefits does data governance bring?
The importance of data governance also lies in its advantages:
- Provides access to extensive experience in data protection.
- Provides a consistent approach to data protection issues.
- Provides educational resources on data protection.
- It helps with compliance with current data privacy regulations and standards (GDPR, HIPAA, among others), to ensure security for customers and avoid legal risks and fines.
Regarding this last point, Government and data protection are currently focused on strict policies and regulations, such as the GDPR in the European Union or the California Consumer Privacy Act in the United States.
For example, in Argentina, it is governed by the Law 25.326 on Personal Data Protection, in Colombia, for the Law 1581, and in Chile for the Law 19.698The common point is that organizations must comply with the regulations applicable in their area of influence, to protect the privacy of citizens' data.
Data governance best practices
To establish a robust governance structure that enables an organization to maximize the value of its data and mitigate the risks associated with its use, it is important to consider some best practices.
These include the following:
- Establish clear roles and specific responsibilities for those who manage and have access to an organization's data. For example, profiles such as the Data Steward, the Data Custodian and the Data Owner, but mainly the Data Protection Officer (DPO).
- Create policies and standards that address data quality, security, privacy, regulatory compliance and other relevant management aspects.
- Establish processes and procedures for the capture, storage, processing, analysis and elimination of data, ensuring its integrity and reliability.
- Training and awareness on the importance of data governance, and the specific policies and procedures of each organization. An action that can be developed internally within a company, and extended to customers and suppliers that interact with its systems and applications.
- Carry out regular assessments to ensure compliance with data governance policies and standards, as well as to perform ongoing monitoring to identify and address potential issues.
- Develop a Data Governance Framework, including decision-making structures, governance committees and conflict resolution mechanisms.
- Promote the collaboration between teams from different areas of the company (business, IT, regulatory compliance and information security, among others), to ensure effective implementation.
- Promote and maintain the transparency in data management, providing access to related policies, standards and procedures to all interested parties.
In relation to the practices contemplated in various regulations such as the General Data Protection Regulation (GDPR) of the European Union, Law 25.326 on Personal Data Protection in Argentina, the Personal Data Protection Law of Brazil, and the California Consumer Privacy Act (CCPA), we can highlight the following:
- Implement appropriate technical and organizational measures to ensure data security and privacy, such as pseudonymization, encryption, data protection impact assessment, and establishment of internal data protection policies.
- Informing people about how their data is being used, obtaining their explicit consent before collecting, processing or sharing their personal data.
- Ensure transparency in the handling of information by notifying data owners of the purpose and the way in which their data will be used.
- Establish robust data management practices by businesses to ensure the protection and privacy of consumers' personal information.
- Implement appropriate security measures to prevent unauthorized access or exposure of such information.
- Designate a data protection officer, generally referred to as Data Protection Officer (DPO), to monitor compliance with regulations.
How is a data governance project developed?
A data governance project begins with an initial assessment to determine the starting point.
Topics such as privacy, technical issues, team composition, and the organization's data culture, among other aspects, are discussed.
From there, the actions to be taken are planned on the following issues:
1. Legal shielding of the organization in terms of data privacy, always prioritizing the business.
2. Creating clear and concise policies that establish the rules and guidelines for data management in the organization. This includes defining roles and responsibilities, establishing data quality and security standards, and ensuring regulatory compliance.
3. Selection and implementation of technological tools and platforms that support data governance initiatives such as data quality solutions, data catalogs, metadata management, and data lineage.
4. Definition and documentation of processes and procedures for data management across the organization. This includes creating policies for data capture, storage, cleansing, integration, analysis and distribution.
5. Development and execution of training and awareness programs on the importance of data governance and how to apply it in your daily work.
6. Realization of periodic audits to assess compliance with data governance policies and procedures, identify areas for improvement, and mitigate risks. This includes reviewing data quality, security, regulatory compliance, and the effectiveness of established processes.
7. Establish continuous monitoring mechanisms (metrics) that ensure the effectiveness and adaptability of data governance practices as business needs and environments evolve.
8. Data Architecture Review, seeking to make it robust and scalable, and to facilitate the capture, storage, integration and analysis of data in an efficient manner. It includes the analysis of the design of data models, through the identification of data sources and the definition of appropriate flows.
9. Generation of data and governance strategy that Align business and IT objectives with data governance initiatives. It involves identifying the organization's needs and priorities, defining the relevant KPIs and establishing an action plan to implement and maintain data governance effectively.
Data Protection Officer: a central role in governance
Following its inclusion in regulations related to data protection and management, and in light of the need to have a data protection officer in increasingly complex scenarios, the role of Data Protection Officer (DPO) is becoming increasingly important.
In fact, an organization that processes special categories of personal data on a large scale must fill this role.
Its specific functions are:
- Monitor compliance with current regulations.
- Indicate, for the specific case, what the obligations are with respect to the processing activities being carried out.
- Conduct and supervise the Personal Impact Assessments (PIA) carried out in the company.
- Cooperate and communicate, if necessary, with the enforcement authority.
As we anticipated, many organizations are required by current regulations to assign a member of their staff for these purposes.
However, due to resource constraints, the lack of a profile with the necessary technical knowledge and skills, or because hiring a full-time data protection expert is beyond the available budget, some regulations such as the General Data Protection Regulation (GDPR) of the European Union, contemplate provisions to fill the position externally.
One way we do this is through our Data Protection Officer consultancy service, which provides organisations with access to specialist knowledge in all aspects of data protection, fulfilling all the roles and responsibilities of an internal DPO, and ensuring compliance with relevant regulations and robust protection of sensitive data.
Conclusion
At IT Patagonia we believe in the power of data to drive business growth, but also in the fundamental importance of data governance and privacy.
We understand that the correct management of data is crucial in today's world, and that is why from our area of Data Innovation We focus on developing solutions that not only maximize the value of data, but also ensure its security and regulatory compliance.
We are committed to continuing to promote good practices in this area and in contribute to the development of professionals trained in this crucial discipline.
