Data—in its raw and unfiltered form—isn’t always safe, secure, accurate, compliant, and available when needed.
In other words, it can be a liability if not properly managed. To make the most of your data, applying an agile method to governance is key.
That means defining policies and procedures, monitoring data usage, ensuring compliance with various regulatory entities, and applying changes iteratively.
While this may all seem daunting, there is a tried-and-true system to get started…
Data governance is essentially the process by which organisations manage the availability, integrity, usability, and security of data assets in enterprise systems. It includes everything from planning and policy development to implementation and maintenance.
Data governance ensures that data is used effectively and efficiently while protecting against misuse or loss across the organisation.
Data governance is often confused with information security.
In reality, they are two different things:
For example, an organisation might have a data governance plan that outlines what types of data will be collected, where it will be stored, who has access to it, etc. This ensures that only the right people can access the correct data at the right time.
A good data governance framework comprises several crucial aspects, but three components in particular demand the most attention:
Policy development involves creating and maintaining policies that define how data is created, accessed, shared, and destroyed.
As well as who can take certain actions.
These policies are written as part of a larger data strategy document. They outline the rules and regulations that govern how data is handled within an organisation.
For example, policies may include items like:
Ideally, these questions aren’t just answered on a Word file but embedded within an ERP system or data platform with granular permissions that fit the enterprise’s needs.
Planning and implementation cover the actual processes involved in implementing data governance.
A typical data governance plan would include developing a set of policies and then implementing them through various deployment stages.
Some common phases include:
Once again, most of these can be achieved with a data platform like Datavid Rover, where all your enterprise data comes together to tell a unified story.
Monitoring and reporting refer to the ongoing monitoring and evaluation of data governance activities.
You can do it manually or automatically using software tools.
However, an effective data governance program requires regular review and adjustment to ensure that all policies are followed.
For example, suppose a company collects customer data.
In that case, it needs to know whether this data is being adequately secured, who has access to it, and when they should delete it.
This kind of oversight helps companies avoid costly mistakes and protect themselves from potential legal liabilities.
In a word, yes! Agile methods are ideal for managing data because they allow teams to collaborate closely to create value.
Here are some ways that Agile can help:
There are many additional benefits, but consider the ones above the key outcomes of a successful data governance framework that leverages agile.
The most effective agile data governance framework comprises five foundational stages.
The best part is that each stage is tailor-made to build off the previous, ensuring that your data governance program grows in value over time.
Your first assignment is to ensure you understand how agile applies to data governance.
It helps you decide whether agile is a good fit for your organization and, if so, which parts of your current data governance process could benefit from agile.
To do this, ask yourself these questions:
While agile methods are based on 4 core principles, the idea is to build an extension of them as part of your internal culture to extract the most value from each session.
Once you know where you stand regarding agile and data governance, it’s time to integrate them and set clear-cut goals. This step includes defining success for both agile and data management.
You also want to define the roles and responsibilities of everyone involved.
If you’re going to achieve your monthly, quarterly, and annual targets, you must implement airtight strategies to support this ambition.
These include:
Check back on these often; don’t let them sit in a Google document untouched for months. Without consistent reviews, people can lose track of the higher-level goal.
The third step involves ensuring people embrace agile within the company culture.
If you’ve already decided it’s the right way to move forward, make sure you spend time educating people on what’s going to change and what’ll stay the same:
Agile is a matter of people and collaboration above all, so it won’t be beneficial to skip this step and get to implementing the processes without telling anyone.
The fourth step is to assess your current framework and determine whether it makes sense to continue using it.
If your current framework doesn’t align with Agile, you may need to replace it altogether or make significant changes to it.
For example, if your current data governance program lacks transparency, you might add a dashboard to show stakeholders how well each project is progressing.
Or, if you don’t have a formal approval process, you might introduce a simple review board.
If you feel that your current framework works fine but still want to improve it, you should consider creating a new one.
And if you decide to start from scratch, you’ll need to develop a new framework that fits your organisational needs and ambitions.
Once you’ve completed all four steps, you can implement your agile data governance program! But before you dive in, take a moment to think about what you’d like to see happen next.
These questions will help guide your efforts.
Now that you know what you want to achieve, it’s time to share your vision.
Start by sharing your ideas with your team members and managers. Ask them to give their input and suggestions; they may offer insights that you hadn’t considered.
Next, ask your customers and users what they think.
Do they agree with your proposed improvements?
Are there any other areas for improvement?
Hopefully, this guide on agile data governance has helped you better understand the concept and provided a roadmap for getting started.
We hope you find this resource useful, whether you want to make small changes or embark on an ambitious project.
And if you need additional guidance, Datavid is here to help.
As a data consulting company that delivered 30+ successful, large-scale data projects between 2020 and 2023, Datavid can help you make the right data decisions. Both from a business and a technical standpoint.
Implementing a good data governance framework means investing in years of successful delivery and increasing exclusive value for your enterprise. Take the first step!