5 Key Data Governance Principles for Effective Data Management

Digitalization has led to more data collection, integral to many industries from healthcare diagnoses to financial transactions. For instance, hospitals use data governance practices to break siloed data and decrease the risk of misdiagnosis or treatment delays. Therefore, managing data to protect its integrity and security leads to high-quality, reliable data that empowers organizations to make informed decisions. Also, protecting the rights and interests of both the organizations processing the data and the individuals whose data is being processed is equally important. As a result, processes and standards have been developed to manage or govern this data effectively.

Data governance is a process of managing data within an organization, as it defines how data is stored, archived, backed up, protected, and accessed by authorized personnel. Effective data governance relies on established principles and frameworks that guide the organization’s data management strategy and act as a foundation to ensure consistency, accessibility, and reliability of data.

Data Governance Principles  

Data governance principles act as a blueprint for managing the data, and facilitate decision-making regarding data storage, access, and use.  

This article will focus on five basic data governance principles essential in implementing a practical framework.  

1. Accountability  

Accountability refers to the clear assignment of responsibility for data-centric activities and decisions within a company. It ensures that individuals and teams comprehend their responsibilities in managing and protecting data assets.

It enables organizations to pinpoint areas of improvement and make necessary adjustments to enhance data governance practices by holding individuals accountable for their responsibilities.

The most critical step in establishing accountability is incorporating strategies and mechanisms, like data validation rules, data cleansing processes, and regular data audits. These mechanisms verify and maintain data accuracy throughout its lifecycle, from collection and entry to storage and use.

2. Standardized Rules and Regulations  

It refers to consistent guidelines and procedures for data management throughout an organization. Standardized rules and regulations create a consistent data handling approach, like utilizing same methods for data entry, access, and storage, across different departments, removing the variations in practices.  

Standardization starts with a common language by creating a centralized data glossary that serves as a single source of truth for data definitions. Also, establishing data classification schemes to categorize data based on sensitivity, security requirements, and access controls, directly translates into actionable data validation rules.  

3. Data Quality Standards  

Data quality standards are guidelines within a data governance framework to ensure that the data used for business processes is high quality, reliable, and fit for its intended purpose.

When data quality standards are in place, employees can confidently use data to analyze trends, identify opportunities, and mitigate risks. High-quality data enables informed decision-making by providing reliable information to individuals within the organization.

Implementing data quality requires key dimensions like accuracy, completeness, and timeliness. To achieve these dimensions, establish data cleansing procedures, both manual and automated, to address existing inaccuracies and schedule regular cleansing activities.

4. Data Compliance  

In data governance, organizations must comply with all relevant data laws, regulations, and industry standards. An effective data governance program must include comprehensive policies and procedures that guarantee ongoing compliance.

These policies should address data collection, processing, storage, transmission, disposal, access, and privacy. Moreover, these compliance strategies should adapt and respond to the evolving needs.

To implement data compliance, conduct regular audits, risk assessments, and compliance checks to ensure they follow all applicable laws and regulations. Additionally, they should regularly train employees on data compliance to integrate compliance into the organization’s culture.

5. Transparency  

Data transparency in the context of data governance principles refers to making all data governance processes and actions within an organization clear and accessible to stakeholders.

Transparent governance processes ensure stakeholders understand how data is managed, who is responsible for it, and who has access to it. This understanding promotes accountability and ensures that everyone within the organization knows their roles and responsibilities regarding data governance.

Achieving transparency in a data governance framework is a three-step process.

• First, develop clear and accessible data policies that outline data collection practices, usage guidelines, and user permissions.
• Next, establish communication channels to keep stakeholders informed about data governance initiatives, including data inventory updates and changes to data access protocols.
• Finally, implement data access request processes that are clear, documented, and readily available to all authorized personnel.

Conclusion 

An effective data governance program facilitates informed decision making by making sure that data is accurate and reliable. Every organization needs a basic set of principles or guidelines to build their data governance strategy. Implementing these principles promotes a culture of data responsibility, guarantees data quality and consistency. Organizations that adopt and regularly assess the effectiveness of these principles lay a solid groundwork for data management. 

Although the basic data governance principles are essential, a successful framework requires customization to the organization’s unique needs. This tailoring and customization can be done utilizing the right tool. 

LIKE.TG offers a complete data management suite to simplify and customize data governance for businesses. It allows clear assignment of roles, ensures that data stewards and owners can easily monitor the data, and aids in transparency of data related actions.  

LIKE.TG enables a strong data governance framework to manage and utilize your data assets proactively. Start a 14-day free trial to explore LIKE.TG’s data management and governance solutions.