Data democratisation: what is it and why are businesses doing it?

What’s data democratisation?

Data democratisation has become a popular industry phrase over the past couple of years. But what does “data democratisation” mean?

“Democratisation” is the act of making something accessible to everyone.

A company’s data assets, of course, are a resource that shouldn’t always be freely accessed by everyone, because it can be sensitive. So when we talk about “data democratisation,” we mean that we’re making an organisation’s data accessible to everyone within that organisation who needs it, in as much as it’s practical and safe to do so.

Why are businesses doing it?

Using data to inform business decisions gets businesses better results. McKinsey reports that data-driven companies are 23 times more likely to top their competitors in customer acquisition and 19 times more likely to stay profitable.

It seems obvious, then, that those who make business decisions ought to have unobstructed access to the data that can best inform them. They shouldn’t have to make a request to internal IT. They should just be able to access the information they need. That’s the contention of data democratisation.

How do you democratise your data?

Most data democratisation projects will begin with setting clear goals. More than likely, your company has a strategy. Your data democratisation project should have clear goals that support that strategy.

But once you know your goals, you have to start with the data. Data democratisation means supercharging how much you use and rely upon your data assets, so the old adage “garbage in, garbage out” has never been more important. That means that goal-setting should be followed by a comprehensive data audit, so you know everything about the data you’re working with. Where is it? How much is there? What is its quality like?

Then, the organisation’s data needs to be brought into a central hub — many organisations prefer a cloud solution, because it’s scalable and cost effective.

Keen attention must be paid to the role of data governance, so your policies must be executed appropriately and with consideration for your goals as well as your compliance and security obligations.

Lastly, the staff who need to use this data need to be trained in access, data security, and use of the data resources now at their fingertips. It serves nobody to make all this data accessible to people who haven’t the skills to use it!

What are the challenges of data democratisation?

While there are plenty of technical challenges associated with data democratisation, the biggest challenge is usually balancing the need for access with the need for privacy, compliance and data security.

The core contention of data democratisation is that everyone who needs to use data ought to have unobstructed access to it, but data is also vulnerable to exposure. That means that decisions must be made about appropriate levels of access, and then those decisions need to be enforced. Businesses have to ask questions like, “Who needs this access?” and “How much access should they have?”

Generally speaking, compliance and privacy challenges are resolved via permissions-based access to data solutions, but strong data governance forms a central pillar of successful data democratisation efforts.

The more technical challenges of data democratisation relate to the engineering problem of taking data from different places, collating it together, and turning it into a data set that is fit for purpose for its end users—the analysts and business decision-makers of the business!

Data democratisation enhances business performance

Data democratisation will make your business run better.

It makes decision-makers more flexible and businesses more dynamic in response to a changeable market landscape. It comes with some challenges, but it’s a very worthwhile goal.

However, the process of transformation from siloed, inaccessible data to centralised, democratised data can be complex and resource intensive. That’s where a qualified, trusted data expert can make or break your project.

Mei Ying Liew is a data expert and DCA’s Head of Data Services

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