A data governance model is a system that is implemented to control how an organization’s information technology (IT) systems are built, used, and maintained. Its primary objective is to ensure compliance with data policies and rules set by the company, while also improving productivity in line with business goals.
Creating a data governance model is no easy feat because of its far-reaching implications for businesses of all sizes and types.
In this article, we cover the basics of a data governance model and data governance best practices!
Why is Data Governance Important?
Sometimes, we tend to overlook how important data is – it’s worth billions of dollars to organizations worldwide!
There are many reasons why data needs to be governed, but chief among them are security concerns and the risk of breaking compliance and other regulations.
Even if your company’s data isn’t worth billions and doesn’t deal with sensitive or regulated data, it can still be beneficial to have a set of rules that govern how that information is handled.
Using a governance model will help you reduce redundancies and inefficiencies within your company while raising data-driven productivity.
A data governance model can be beneficial to your business, but the question is: how do you create one?
How to Create a Data Governance Plan
Creating a data governance model is an involved process that requires careful considerations and planning. Many companies become the victims of the most common data governance mistakes, such as treating data governance as a technology project.
Creating a data governance model is an involved process that requires careful considerations and planning. Here are some of the most important aspects that should be included in your governance plan.
1. Build a roadmap
Think of your data governance plan as a map you can use to find your way between two points.
To create a data governance plan that works, you have to get clear on where you are now, where you want to be, and how you expect to get there. This information will help guide your data governance efforts appropriately.
Use it as a roadmap for success!
2. Incorporate business goals into your roadmap
As you develop your roadmap, keep in mind that your data governance efforts should be in line with business goals. After all, it’s pointless to build a data-driven system if it doesn’t align with what the business needs.
Many companies mistakenly assume that their company’s existing data management systems can be used as-is for building a data governance model.
If the company itself isn’t ready – either in terms of infrastructure or strategy – then it can be difficult to remedy that after you’ve already started building your data governance plan.
3. Identify redundancies and inefficiencies
As you go over your current state of data management, look out for redundancies and inefficiencies.
What is there vs. what isn’t there?
What should be vs. what shouldn’t be in X place?
Is there anything that is slower than it actually should be?
How can we improve the (current) best version of our data management even further?
These are the primary areas you’ll want to improve upon since they involve changing how information is collected or handled.
4. Determine how to achieve compliance, security, and productivity
As you develop your roadmap, determine how to achieve compliance, security, and productivity. This will be critical in determining the goals of your data governance model.
You’ll need to work closely with your legal and compliance officers as you create a data governance model, especially if you’re dealing with regulated or sensitive information.
This ensures that nothing falls through the cracks, but it can also be challenging because of time constraints and other factors.
To stay ahead of your competitors, make sure to equip your company with an exceptional data governance model. If you’re unsure where to start, HICO-Group can show you the way. Get in touch with us to establish a data governance strategy in your company and ensure data-driven decision-making all the way.
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