Why establishing a data governance framework matters for organizations  

As organizations continue to experience exponential data growth, one of the biggest challenges they face is not only managing data but ensuring the entire process is effective. While there are many data management tools available in the market today, organizations must pick a data management platform that can assure data governance.

Gartner refers to data governance as the specification of decision rights and an accountability framework to ensure the appropriate behavior in the valuation, creation, consumption and control of data and analytics. Unlike data sovereignty, which is also an important consideration for organizations, the main goal of data governance is to ensure that data is accurate, trustworthy, and can be used effectively by the organization to achieve its goals.

As data governance provides a framework for managing data effectively throughout its lifecycle, from creation to deletion, organizations need to consider the following reasons.

• Regulatory compliance – As with any data, organizations need to understand the laws that come with the data, especially in how they use it. Many industries, such as healthcare and finance, have strict regulations for how data must be collected, stored, and used. Data governance ensures that organizations comply with these regulations, reducing the risk of fines and legal action.
• Risk management – As data breaches and other security incidents can have severe consequences for organizations, including damage to reputation, loss of customer trust, and financial losses, data governance helps organizations identify and manage data-related risks to minimize these negative impacts.
• Data quality – Most data collected is often unstructured and in a silo. Data that is inaccurate or incomplete can lead to poor decision-making and inefficiencies. Data governance helps organizations establish processes for ensuring data quality, such as data validation and data cleansing.
• Collaboration and efficiency: To deal with the problems of data in a silo, data governance establishes standards and processes for data sharing, integration, and management, enabling better collaboration and faster decision-making.

Despite this, a big challenge to ensuring data governance for organizations comes from data complexity, especially in data architecture. As organizations take a multi-cloud or hybrid cloud approach, moving the data from one cloud to another can be complex and complicated. Data management vendors continue to address these issues and have come up with various solutions to simplify the problem.

Other challenges include ensuring regulations and compliance is met when working with multiple data as well as the cost. Implementing data governance can be expensive, requiring investment in technology, personnel, and training. This can be a barrier for some organizations, particularly smaller ones with limited budgets.

This is also where data sovereignty comes into play. Data sovereignty refers to data that is subject to the laws and regulations of the country or region in which it is located. In practice, data sovereignty can influence data governance. For example, if an organization is subject to data sovereignty laws that require personal data to be stored within a particular country or region, the organization must implement data governance policies and procedures that ensure compliance with those laws, such as encryption or access controls.

So how can organizations ensure proper data governance?

While there is no easy way to manage data and deal with data governance, organizations should look to establish a data governance framework. The data governance framework outlines the policies, processes, and procedures for managing data.

This framework should also define data ownership, establish data standards and definitions, outline data security measures, and identify data-related risks and compliance requirements.

Tech vendors that are focused on helping organizations plan a data governance framework include IBM, Oracle, SAP, Atlan, Alation, Informatica, Cloudera, Colibra and Talend. Each of these tech vendors has its own unique way of ensuring organizations can come up with a framework that meets their business needs.

In conclusion, organizations must be committed to investing the necessary resources and expertise to ensure that their data is accurate, secure, and compliant with regulations.

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