Whether you recognize the term or not, just about every business is undergoing some form of digital transformation these days. The need to use data more efficiently is often the driving force behind digital transformation, and that efficiency tends to come from making the move to the cloud.
As a result, many of the technology staples that businesses have historically built their IT infrastructure around are changing, or disappearing altogether. This is especially true where security is concerned. There was a time when protecting business data meant building up perimeter defenses that focused on your systems and network. But with traditional data storage solutions being replaced by cloud technology, that perimeter no longer exists for many businesses – meaning security needs to shift to the data layer in order to be effective.
But before you tackle new data security measures, you first have to figure out how you’ll be collecting, storing, analyzing, and utilizing your business data. Data quality is at the center of successful digital transformation, especially when your intention is to become an analytics-led, or data-led, company. Achieving that can be as simple as updating your infrastructure and adopting new applications, or it can require major changes to your business model.
Where analytics applications were once used to go over data after the fact, many new applications provide real-time feedback and need to be worked into your day-to-day operations in order to be effective. They also require you to be able to access data from any source, whether that’s on-premise, in the cloud, or in any other new data platform. And most importantly, these considerations need to be made right from the start of the digital transformation process. Data governance cannot be an afterthought if you want to succeed.
The first step towards ensuring data quality is figuring out how best to pull data from multiple sources into a centralized data repository. Once that system has been established, it becomes a matter of figuring out which of your data sets are incomplete or incorrect in their current format. This is a common problem due to the fact that most databases and applications weren’t built with the intention of having data removed for other uses. Issues like inconsistent file names or missing customer IDs need to be identified and dealt with.
After that, the problem becomes figuring out not just how to make sense of your data, but have your data make sense in relation to your business. Transforming raw data into information you can use to pick out something like customer purchasing habits goes back to data governance, and more often than not requires expertise and guidance from an outside source such as your IT support provider.
Of course, digital transformation is about more than just data quality. There are other factors that can impact your business’ success with this type of endeavor, such as your approach to cloud technology. Building your cloud-based infrastructure using applications that are cloud-native – meaning they were built specifically for the cloud – will give you a much better result than integrating your existing solutions into a cloud platform. That’s not to say that integration can’t be successful, but it can often require a little finessing to get your systems working the way you need them to.
And that brings us back to data security. Whether your data layer is on-premise or in the cloud, it’s that layer that hackers are interested in – not your systems themselves. Having a real-time and crystal clear view of exactly where all of your important data is will allow you to build defenses around the data itself. With effective data quality and data governance in place, you’ll never have to wonder if an important database has been overlooked, and therefore can feel confident in your data security.
Data quality isn’t just the key to digital transformation success; it’s the key to better security, better productivity, and a better business.