In today's digital age, the value of data cannot be understated. Businesses are relying more and more on data to make informed decisions, whether that be for marketing, internal operations, or sales strategies.
As a result, there has never been a greater need to manage and control data assets, ensuring data can perform competitively to its full potential. This is where data governance comes in. An empowering practice that encompasses the processes, policies, and procedures that ensure data quality, integrity, and compliance.
As businesses embark on their digital transformation journeys, the significance of data governance becomes increasingly apparent. In this guide, we’ll explore the importance of data governance and how to apply this transformational practice to your business.
What is data governance?
Data governance (DG) is the overall management and control of an organisation's data assets. It involves a combination of processes, policies, technologies and systems that help ensure the quality, integrity and security of an organisation’s data. For instance, this may involve measures to prevent data errors, validate data inputs, and establish clear data quality metrics.
When implementing data governance practices, organisations will typically define roles and responsibilities, and establish rules and guidelines for data-related activities. A well-designed data governance strategy usually includes a data governance team that acts as data stewards, ensuring processes are set up and managed correctly.
The main objective of data governance is to ensure that data can perform for its intended purpose. For example, a business could only personalise its marketing activities if it had accurate, relevant, and organised information about its customers. Data governance allows for this, keeping accountability of data quality issues and reducing the room for error.
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Data governance and compliance
Another focus of data governance is compliance with data laws and regulations, such as the General Data Protection Regulation (GDPR). For instance, establishing policies and procedures to protect sensitive data from unauthorised access, breaches, and misuse. Additionally, allocating who in the business is able to access specific data, and what they can do with it.
This ensures that an organisation's data practices adhere to relevant laws, regulations, and industry standards.
Data governance and data quality
Data governance and data quality are intertwined but distinct concepts. Data governance sets the framework for managing data through policies, processes, and roles to ensure data integrity, security, and compliance. Data quality ensures that the data itself is accurate, complete, consistent, timely, valid, and unique.
While data governance provides the structure and rules, data quality measures how well data adheres to these standards. Together, they ensure reliable data for informed decision-making. For more details, see our blog on data governance and data quality.
Do you need data governance?
Data governance is considered essential for organisations that aim to effectively manage their data assets and drive value from them. Without it, it’s not possible to truly understand how data assets are benefiting the business. And even more detrimentally, the opportunities that await.
When we think about data, it’s important to see it not only as an asset, but a vital driver within the business. Some of the most pressing business challenges can be overcome with data solutions: identifying and rectifying revenue leakage, credit risk and collections performance, optimising customer value with value based management, data cleansing, and so much more.
Data governance acts as the foundation for leveraging data as a strategic resource, allowing businesses to address critical challenges effectively and identify opportunities for growth.
This can help with things such as which specific products or services to focus on, and how to position them. Additionally, customer trends, and which areas of the business to allocate funds. This can result in increased revenue and can reduce the chance of making ill-informed decisions.
Benefits of data governance
Effective data governance can help organisations:
- Improve data quality: Data governance puts a data quality management plan in place that improves data accuracy, consistency, and ensures data is complete.
- Maximise the value of data: Organisations can get the very most out of their data, by ensuring it’s complete and reliable.
- Make informed data-driven decisions: Organisations can make the right decisions at the right times to increase performance and revenue based on their data.
- Improve data management: It establishes codes of conduct and best practices for data management, ensuring everything is formatted consistently and that it’s fully compliant.
- Improve operational efficiency: Those who need the data can easily access it and find what they need, reducing the amount of time spent searching for things or not being able to find them at all.
- Be data compliant: Creates a platform for organisations to make sure they are fully compliant with GDPR and any other regulations.
- Determine policies: Knowing exactly what to include when looking at data management.
- Create a data map: The potential to know exactly where all data is located makes it easier to navigate and find exactly what you need.
- Mitigates risks: Can help businesses understand, assess, and mitigate organisational risks by ensuring that data is managed and used correctly avoiding data breaches, loss and any type of non-compliance.
- Increase revenue: Being able to use the data to make informed decisions can help businesses increase profits.
Data governance vs data management
Data governance and data management are regularly used interchangeably, but these are two different concepts. Data governance is part of the overall management of data and puts all the policies and procedures in place.
Data management focuses more on executing the rules and policies set out by data governance. Without data management, data governance is just documentation. You can think of it as the plan or blueprint to build something, while data management is the act of building it. You could build something without a blueprint is still possible, however it may not be as structurally sound or built as efficiently, and the same applies to your data.
Data governance roles and responsibilities
There are usually multiple people involved in a data governance strategy. A data governance team will typically be responsible for implementing and enforcing it. This will often be broken down into four roles:
1. Data admin
The data governance strategy is overseen by the data administrators who manage the implementation of it. They will be the main point of contact for any data related issues that need resolving. If there is a Chief Data Officer (CDO), they typically are accountable for the success or failure of a data governance program.
2. Data steward
Their main responsibility is to ensure that business users can consistently access high-quality data and are a bridge between business and IT. They keep track of ever-changing data governance regulations by reviewing data governance policy, processes and how it’s been implemented.
3. Data custodian
They have a very similar role to a data steward. They control who accesses data managing permissions and oversee data storage. They will work closely with stewards to correct any data quality issues.
4. Data user
This is anyone within an organisation who uses the data to get value from it. This includes marketers, researchers, executives, business managers and more.
Data governance best practices
Here are some helpful tips for data governance to make sure your business if following it correctly:
1. Set clear and measurable goals for your organisation
2. Gain a comprehensive understanding of the steps required to be compliant
3. Secure early support and involvement from management and executives
4. Deploy a strong and comprehensive data governance framework
5. Identify and define all data domains within your organisation
6. Provide training to all staff, emphasising the importance of data governance
7. Document and track progress made in implementing data governance initiatives
8. Invest in technology that will help your data governance program work effectively
What data governance solutions are available?
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