Data Governance refers to the framework, policies, and procedures ensuring data availability, usability, integrity, and security within an organization. It establishes accountability for data-related processes, ensuring compliance and effective decision-making. That is why its role is indispensable for organizations to manage their data throughout its life cycle, from acquisition, usability, data security, and integrity.
Data governance offers transparency and protection against ineffective data management and ensures adherence to regulatory requirements, mitigating risks associated with data misuse, breaches, or non-compliance. Let’s see this in more detail:
Low data quality impacts every business element, from marketing insights to financial planning, and impedes the achievement of crucial KPIs. When data quality is inadequate, making informed decisions or taking reasonable risks is impossible.
In the other way around, Data Governance practices help organizations maintain data accuracy, consistency, and reliability, reducing the risk of errors and enhancing trust in organizational data.
The increasing complexity of the regulatory environment has increased the importance of companies establishing robust data governance policies.
That is why Data Governance can help companies prevent risks connected with noncompliance while anticipating future requirements proactively. Implementing a data governance strategy facilitates your organisation's compliance with the most recent laws, such as the General Data Protection Regulation (GDPR) of the European Union, the Health Insurance Portability and Accountability Act (HIPAA), the Payment Card Industry Data Security Standard (PCI-DSS), and others.
Reliable data, governed properly, forms the basis for informed decision-making, enabling strategic planning and execution.
This process involves several key components:
Establishing Policies and Standards: Defining clear guidelines and standards for data management, including data access, usage, and security protocols.
Defining Roles and Responsibilities: Assigning accountability for data quality, security, and compliance to specific individuals or teams within the organization.
Data Lifecycle Management: Outlining processes for data collection, storage, usage, and archival or disposal in line with regulatory requirements and organizational needs.
Monitoring and Enforcement: Regularly monitoring adherence to policies, conducting audits, and enforcing governance measures to maintain data integrity and security.
Now that businesses can collect vast quantities of heterogeneous internal and external data, they require discipline to optimise their value, mitigate risks, and decrease costs.
Trackingplan is an always up-to-date single source of truth and data governance tool. Its automated capabilities bolster Data Governance in two key ways:
By automating data validation, quality checks, and access controls, it minimizes manual efforts and diminishes the likelihood of human errors.
Automated monitoring ensures a continuous alignment with data governance policies and regulatory standards.
Moreover, it eliminates the reliance on outdated spreadsheets and ensures the continuous cleanliness and adherence to expected specifications of the data added to your data warehouse. Moreover, Trackingplan aids in the exploration, comprehension, and documentation of your data, fostering improved team communication.