The key to successfully using AI is data quality and availability, which means you need a data governance strategy Here’s how your business can get started.  

 

Artificial intelligence is the latest tech buzzword and businesses are scrambling to find ways to implement and leverage it in a variety of ways. Whether you’re using AI for forecasting, marketing, or even to chat with your customers, the one thing you need is data – and lots of it. Without accurate and accessible data, your AI efforts are bound to fall flat.

This is why data governance is so crucial to the success of any AI application, no matter how big or small. If you have bad data, you’ll end up with bad results. If you have good data, you might be able to truly revolutionize your organization.

Joe Bester with Atlanta IT Support company, 360 Smart Networks take a look at exactly what data governance is and isn’t, and how to make sure your business can get started with it.

What Exactly is Data Governance?

Simply put, data governance is an overall strategy that encompasses all aspects of your data assets. This includes how you collect data, where you store it, how it gets used, and what happens if data is lost or corrupted. A good data governance program makes your data management less costly and more efficient. Most importantly, it ensures that your data is clean and well-organized, which allows your AI processes to run smoothly.

What’s the Difference Between Data Governance and Management?

One thing to keep in mind is that data governance is not the same as data management. Data management is more of the task of keeping your data ready and available to use. Data governance is an organizational strategy. It requires carefully constructed policies and buy-in across all levels of the business. It’s much bigger and more important than simply managing your data. You should look at data management as a small piece of your organization’s overall data governance strategy.

How Do I Get Started With Data Governance?

Data governance is not something you can set in place overnight and forget about. Like any other business strategy, it requires thorough planning and constant evolution. However, here are some important best practices to help you get off the ground with your data governance:

  • Mold it into your organization – there’s no one-size-fits-all operating model for data governance. If your organization has a centralized leadership model, the structure of your data governance should be centralized, too. The key is to make sure data from every aspect of the business has a clear owner who is ready and able to take full ownership.
  • Define your data – the next step of establishing data governance is breaking your data into carefully considered segments. Start big. A good example might be breaking your data into customer data, company data, and vendor data. From there, you can break it into smaller pieces and develop policies and procedures based on the handling of each different segment of data.
  • Develop controls – one of the most important aspects of data governance will be the controls. You must develop processes for collection, storage, and use of data. These controls must include processes for monitoring and resolving issues quickly.

 

To help truly bring your organization to the next level, artificial intelligence and data governance must go hand-in-hand. By following the advice above, you’ll be well on your way to a strong data governance strategy and will be ready to successfully leverage AI throughout your organization.