Reimagining the Wheel: Why the Future of Data Management Doesn’t Mean Starting from Scratch

This article was written in collaboration with Scott Chambers, Director, Analytics at NTT DATA Business Solutions.

Imagine your data management approach as a hub and spoke system. Traditionally, the data warehouse has been a hub, requiring all information to be fed into it before things get rolling. The spokes, meanwhile, take in data and transmit it to a centralized location without having to connect to every other network. They work well within that system, but poorly with others – if at all. Information is siloed, processes are often repeated, and your entire operation is less efficient than it has the potential to be. You’re also reliant upon a model that can falter when any component fails.

This fragmented approach risks issues like security lapses, production inconsistencies, and general gridlock. So, while this model is familiar, it’s limiting and doesn’t represent the dynamic atmosphere your business now operates in.

In today’s world, data governance has the power to be inclusive – a way to house and visualize multiple systems seamlessly. And that happens when a cohesive mindset meets cohesive technology, in which systems don’t necessarily have to move data; they just need to be able to access it.

Enter the blended ecosystem — a data fabric — where all the pieces play together.

Possessing and utilizing a robust data fabric is quickly becoming key to every aspect of business, from understanding and predicting consumer trends to discovering connections between seemingly disparate information across departments. It will also be essential as automation expands across industries.

We’re seeing data fabric work in the real world. For example, NTT DATA Business Solutions works with an international food manufacturer that utilizes multiple systems to fit its needs – customer service, sales, ERP, and so on. Through our ongoing discussions with this customer, we quickly realized the data fabric coexistence model helped optimize efficiency. Instead of having a supply chain system that doesn’t work with a quality assurance platform, or whose functions overlap, a data fabric model allows them to work in harmony. And we’re finding there’s much more of an openness and a willingness from software providers to take this approach to data management.

The road forward.

So, how do we all get there and what should happen first? There are a few things that are integral to successful data integration across industries.

First, there needs to be a better understanding of data governance by data stewards, as well as adequate preparation to expand their role. Because we know reliable, accurate data is integral to any major systemic change, CIOs, IT managers and the like will need optimal information before they can be expected to effectively command it.

Companies are constantly adding new systems, new solutions. Before bringing those solutions in, they should ask first how they fit into the governance model. How do they become an asset to the business? How do they enhance the existing data landscape? And how do they leverage that data with the increased use of AI? Answering those questions will give companies a better sense of how well-equipped they are to succeed in what promises to be a continually evolving space.

The foundational principles of good data management remain and will guide the future. The wheel isn’t getting reinvented. It’s getting an upgrade. And from payroll to processes, your data must be up for the ride.