Implementing adequate Data Governance practices represents a pivotal shift in how organizations approach and leverage their data assets. 

While comments on the prevalence and potential of data are ubiquitous today, the truth is that only the right data governance practices can empower organizations to truly unlock the full potential of data. 

The race to implement the fundamental Data Governance best practices is getting more and more fast-paced and intense. As such, firms like McKinsey highlight that the leading data-driven organizations will “naturally and regularly leverage data to support their work” as soon as 2025. 

In order to do so, the true data-driven approach of the future must be intentional and proficient in data management and Data Governance, as only these frameworks allow for an enhanced trust and a mitigation of risks associated with data misuse.

In this context, let’s take a look at 6 crucial Data Governance best practices and the key tools to implement them.

Quality Data Governance: what the right framework looks like

In order to understand the key Data Governance best practices it’s worth looking at what a successful framework looks like in this area. 

Data Governance is defined as the set of practices to ensure the availability, usability, integrity, and security of data within an organization. As such, it involves the creation and enforcement of policies and procedures to ensure that data is consistent, trustworthy, and meets regulatory compliance requirements, with the goal of maximizing the value of an organization’s data assets.

As such, Data Governance ensures:

• Data quality, that is, data that is accurate, complete, and consistent across the organization)
• Data security measures to protect data from unauthorized access, alteration, or destruction
• Data privacy, so that it’s handled in accordance with privacy regulations and guidelines, such as the GDPR or HIPAA
• Data Lifecycle Management, from creation to archival or deletion, including data storage, backup, and retention policies
• Data stewardship, so that responsibility for managing and maintaining specific datasets or data domains is established within the organization
• Data compliance, meaning that data practices align with relevant laws, regulations, and industry standards

In this context, an adequate data governance framework provides a structured approach for managing and controlling an organization's data assets. It will define governance structure, the policies and standards for data management, roles and responsibilities and data management processes throughout its lifecycle. 

Additionally, it will describe the organization's data architecture, Quality Management processes and controls, KPIs and metrics and the tools and technologies that will support data governance activities.

All with one aim: to let organizations access the benefits of an optimized data governance framework, including enhanced data quality, security, compliance and operational efficiency.

Data Governance best practices: 6 fundamental procedures

Having full data visibility

Understanding the nature, source, and characteristics of an organization’s data is fundamental to effective data governance. 

This practice involves a series of processes such as conducting data discovery processes to identify what data there is, where it resides, and how it's used. The aim is to also know the categories this data belongs to and their sensitivity levels, including metadata and unstructured data, which might be harder to track. 

Only by having full visibility of data can organizations enable informed decision-making and risk management, all while ensuring compliance with regulatory requirements.

Organization and systematization

Second in the list of Data Governance best practices comes the need to organize data, which means structuring it in a logical and consistent manner to facilitate easy access, retrieval, and analysis. 

Frameworks, taxonomies, and data dictionaries are all available tools to categorize and define data elements, all with the aim of enhancing efficiency and promoting data quality and consistency.

The end goal is to have a clearly-defined protocol to interpret, classify and process data based on its sensitivity, so that the process works systematically.

Focus on data security and privacy

In an increasingly hostile cyber landscape, privacy and security should be a top priority, so that organizations can safeguard sensitive information and mitigate harmful data breaches.

Privacy and data security should be embedded into every aspect of data governance practices, so that a privacy-by-design and security-by-design approach is guaranteed. 

Lifecycle considerations

Data governance isn't a one-time endeavor, but must be understood as an ongoing process that spans the entire data lifecycle, from creation to disposal. This ensures integrity and compliance is kept over time.

As such, policies and procedures must address the whole lifecycle of data, including data capture, storage, processing, sharing, and archiving. 

Organizations should also take a close look at how these different processes may affect each other. Additionally, the role of data stewards for each stage comes in as a crucial strategy to ensure policies are implemented.

Focus on the people

Data governance must be understood as a collaborative effort that requires participation from all departments and human teams within an organization. As such, good Data Governance practices are a combination of the right processes and technologies, but also of well-trained people. 

As such, a culture of data stewardship and accountability across the organization must be established, so that every link in the chain understands its roles and responsibilities in managing data effectively. 

Establishing clear metrics and KPIs

Measuring the effectiveness and impact of data governance initiatives is key and it can only be achieved through establishing the right metrics and measurable goals, as well as key performance indicators (KPIs). 

These help track progress in the implementation of Data Governance best practices, but also are fundamental to identify areas for improvement.

The role of icaria Data Governance

Automatic and smart technological tools are taking Data Governance to the next level thanks to their capacities to eliminate human errors and automate processes. 

Such is the case of icaria Data Governance, an advanced tool that facilitates the implementation of the best Data Governance practices, ensuring secure, accurate and available data across all business operations.

The platform allows organizations to implement and optimize their Data Governance framework, with the aim at having total control over data. As such, it facilitates the key practices we’ve just mentioned through the following features:

• Ensures the integration of data from a variety of sources but also simplifies its cataloging, ensuring data visibility, organization and accessibility 
• The tool guarantees regulatory compliance through various processes, including  a robust audit system that records all activities performed with your data for enhanced transparency and regulatory compliance
• Identifies and corrects data issues in real-time for total data trust and integrity
• Efficient scalability that grows hand in hand with an organization’s data and its Data Governance needs

As such, icaria Data Governance represents an ally for organizations looking for a reliable Data Governance tool that will be an inestimable aid in employing data organically and safely, and thus accessing all its potential.

The tool is thus a fundamental instrument in enabling stakeholders to make data-driven decisions with confidence and accuracy, driving innovation by providing a solid foundation for operations that drive business growth and competitive advantage.

Want to learn more about our Data Governance tool and how it can optimize your organization’s practices and framework? 

At icaria Technology, we’re at the forefront of facilitating data access and integrity for organizations. 

Get in touch with us and speak to our expert team about the potential of automating your Data Governance processes.