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As the importance of data continues to grow, and the amount of data being processed by organizations grows further, many organizations are beginning to feel the constraints and demands of compliance. Therefore this makes data governance paramount to guarantee the security, accuracy, availability, and usability of your data. Data governance encapsulates the approach to managing data during its lifecycle, from acquisition, to use, to disposal. The primary goal of data governance is to establish a set of procedures to guarantee that data assets are reliable, consistent, and accessible across an organization. This means that all stakeholders of an organization must be involved and cooperate with the rules and processes surrounding data governance.

So to help your comprehension of the term data governance, within this article, we will outline what data governance and data governance as a service (DGaaS) are. As well as outline some common use cases for data governance as a service. In order to assist you in making an appropriate decision regarding the utilization of a data governance tool.


What is Data Governance?

Data governance refers to the overall management and maintenance of the integrity, availability, usability, and security of data within an organization. It includes the processes, framework, and policies that guarantee high data quality and availability while maintaining the data's security and compliance.

Executing effective data governance processes requires collaboration among multiple stakeholders, including IT teams, data managers, business leaders, and compliance officers. A well-structured data governance structure aids organizations in making informed decisions, improving operational efficiency, and reducing risks associated with poor data quality or mismanagement.

What is Data Governance as a Service?

Data Governance as a Service (DGaaS) is a model where a third-party service provider, such as, supplies data governance solutions and services to organizations on a subscription or pay-as-you-go basis. This approach enables companies to outsource their data governance requirements to specialized service providers, who deliver expertise, tools, and frameworks to support the organization's data governance initiatives.

Data Governance: How it works

As previously mentioned, data governance follows a set of rules and principles that the entire organization must adhere to, in order to guarantee effectiveness. To further understand data governance, the term can be broken down into a few key steps.

1. Set up a Governance Framework: This involves outlining the organizational structure for data governance, roles, responsibilities, and decision-making processes.

2. Outlining Objectives and Policies: Understandable objectives and policies are outlined to guarantee data is managed in alignment with business goals. These may cover privacy, data quality, security, compliance, and usage guidelines.

3. Data Inventory and Classification: This step regards understanding your data, how it’s collected, where it’s stored, and how it's used. For effective governance, it's vital to classify data based on its sensitivity, criticality, and compliance requirements.

4. Data Quality Management: Here, you should implement processes and standards to guarantee data accuracy, consistency, and reliability. This involves data profiling, cleansing, and validation.

5. Metadata Management: Maintenance and management of metadata is important to comprehend its context, usage, and relationships. This aids in understanding, discovering, and governing data effectively.

6. Data Security and Compliance: Applying security measures to protect sensitive data from unauthorized access, and ensuring compliance with relevant regulations (e.g., GDPR, HIPAA, etc.).

7. Data Lifecycle Management: Managing and maintaining data from its creation to archiving or deletion, including retention policies and proper disposal.

8. Monitoring and Continuous Improvement: It is important to continue these practices by regularly monitoring data processes, assessing adherence to policies, and making adjustments for continuous improvement.

Data Governance as a Service: Use Cases

There is a broad variety of use cases for organizations wanting to optimize the overall maintenance and management of their data. We have outlined a list of both common and lesser-known use cases to highlight the extensive capabilities of a Data Governance as a Service (DGaaS) solution.

Firstly, a common use case of Data Governance as a Service is for small and medium-sized enterprises (SMEs). This is because most often SMEs are insufficient in regard to resources and expertise for robust in-house data governance. DGaaS can provide these organizations and businesses with access to expert guidance, tools, and frameworks, allowing them to manage their data effectively and efficiently without having to invest in a dedicated internal team.

Another typical use case of Data Governance as a Service is for regulatory compliance. Industries such as healthcare, finance, and e-commerce are subject to stringent regulations (like HIPAA, GDPR, etc.). DGaaS providers guarantee that data governance strategies align with these regulations, aiding organizations to maintain compliance and avoid potential penalties. As well as this regulatory standards can change and evolve. DGaaS providers monitor these changes and update their offerings accordingly, guaranteeing that their clients remain compliant without having to constantly reconfigure their systems and policies.

In addition to the previously mentioned use cases, another use case of Data Governance as a Service is cost and resource optimization. For organizations looking to lessen operational costs or lacking in-house data governance expertise, DGaaS supplies a cost-effective solution. It reduces the requirement for large investments in infrastructure and internal expertise while offering access to professional services on a subscription-based model.

The final use case for Data Governance as a Service that makes our list is cloud migration and management. Organizations and businesses transitioning to cloud-based infrastructures can use DGaaS to guarantee that data governance policies are seamlessly integrated and maintained across the cloud environment.

If you’ve enjoyed this article why not read What is CMMC or Why Log Management is Important for IT Security?

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