Establishing data governance within an organization is a concept that varies depending on the organization’s objectives and the context in which it operates. There is an increasing need for organizations to excel in data, in order to thrive. As we continue our Data Governance Series, this third article delves into the concept of “Building Your Data Governance Framework,” and discusses the importance of establishing a clear framework for data governance within the wider context of implementing effective data management practices.
Our previous article emphasized the significance of data ownership, focusing on understanding who owns and is responsible for data within an organization. Our first article dived into the ‘why’ of data governance, helping organizations to understand the fundamental importance of establishing an effective data governance framework.
As we shift our focus to building data governance frameworks, we will dive into the essential guidelines and practices necessary to uphold data quality, privacy, security, and compliance. We aim to guide you to draw value from your data with the support from data governance, ultimately empowering you to achieve your data goals in a controlled and compliant manner.
What is Data Governance?
While data governance can be broken down and defined in several different ways, the overall consensus is that the implementation of data governance in an organization should form the decision-making process and overall structure of the availability, usability, security, accuracy and integrity of the data available to its employees in order to create value from the data.
Understanding the Importance of Data Governance
You might ask yourself, does my organization need data governance? The answer, most likely, is yes. Not only does an effective data governance ensure compliance with ever-growing and increasingly complex legal regulations, but it also minimizes unnecessary costs, manages risk, minimizes complexity, and improves data literacy.
Timely access to relevant and accurate data is crucial for making informed business decisions. With proper data governance practices in place, organizations can ensure that the right people have access to the right information with fit-for-purpose quality. This empowers decision-makers with reliable insights derived from well-managed and governed data assets.
Accuracy & reliability
Data governance plays a critical role in maintaining the accuracy and reliability of an organization’s data assets. By implementing clear policies, procedures, and guidelines for managing data, a clear framework for data quality management can be established. This ensures that the data used across various departments is consistent, up-to-date, and trustworthy.
Compliance with regulations
In order to ensure effective data management and regulatory compliance, organizations must adhere to various regulatory requirements, including but not limited to GDPR and HIPAA. Data governance plays a crucial role in helping organizations meet these regulatory standards by establishing processes to safeguard sensitive information, implementing robust access controls and maintaining auditable records of data handling procedures.
Clear roles & responsibilities
Implementing a robust data governance framework means that roles and responsibilities can be assigned clearly, so that everyone involved understands their obligations and accountabilities within the framework. This clarity promotes collaboration, reduces confusion, and enables efficient decision-making processes, while also enabling efficient value creation from data.
Protecting data privacy & security
The fundamental pillar of data governance resides in protecting data, and ensuring the privacy and security of sensitive data assets. Classifying data enables organizations to prioritize information based on its sensitivity level. By categorizing data into different levels of protection, organizations can determine how it should be stored, accessed, and shared. Encrypting data assets in transit and at rest adds an extra layer of protection by scrambling the content so that only authorized users with decryption keys can access it.
Data Governance in Practice: Establishing a Data Governance Framework Within Your Organization
When deciding to implement a data governance framework in your organization, the following questions should first be considered:
- Why do we want to implement data governance?
- Where are we now, where do we want to be, and what is the gap between the current state and the target?
- What are our roadblocks to success? How can we overcome these?
- What elements will govern our data governance framework?
- How do we make the appropriate organizational changes to effectively implement the framework?
Let’s look at an example of a company who wishes to become a data-driven organization. They have outlined strategic focus points and business objectives linked to data, however they are facing some challenges. In the text below we outline how data governance and well managed data supports them to tackle the challenges on their path to become data driven.
Strategic focus points:
“Company Ltd” has set goals to be able to make efficient decision-making and to improve overall operational efficiency.
They have identified that in order to achieve this, they need to implement more automation, and make better decisions faster based on data.
The Path to Data Management Excellence
In conclusion, data governance provides a structured framework for organizations to unlock the full potential of their data, playing a pivotal role in ensuring that data is treated as a valuable asset.
Effective data governance goes beyond compliance with legal regulations and compliance; it enables efficient data development processes, which can help the organization in creating value from their data efficiently. It establishes clear roles and responsibilities, promotes collaboration, and enhances data privacy and security. Moreover, data governance helps organizations bridge the gap between their current state and their data-driven aspirations.
By implementing robust data governance, organizations can address common challenges such as a lack of trust in data, inconsistent data quality, and inefficient data development processes. This ensures that data is handled, used, and protected in a systematic and well-documented manner, fostering a culture of data literacy and accountability.
In the ever-evolving data and AI landscape, mastering data governance is not just a best practice; it’s a necessity for organizations looking to thrive and excel in the data-driven era. So, whether you are new to the concept of data governance or looking to enhance your current approach, remember that the path to create value efficiently from your data assets begins with mastering data governance.