Survey: Data Management Issues Hinder Digital Transformations

A survey of 525 enterprise IT executives conducted by 451 Research, a unit of S&P Global, on behalf of Immuta, a provider of data access control tools, published today suggests many organizations are going to have a significant challenge achieving their digital business process transformation goals simply because of the way they have historically managed data.

A full 90% of organizations said their DataOps strategy was not yet optimized. Top challenges cited include a lack of personnel or skills (38%) followed by not enough automation (29%). On the plus side, 85% of respondents say that their data operations (DataOps) strategy is either being accelerated or is at the very least nascent or emerging

Nevertheless, more than half of respondents (55%) said they either “somewhat” or “completely” agree that data is often stale or out-of-date by the time their organization is consumed or analyzed.

The survey also notes 84% of respondents expect data privacy and security requirements over the next 24 months will have an adverse impact on how accessible data can be across their organization. The paradox is that organizations that have been impacted by data privacy regulations appear to be further down the path toward implementing a mature DataOps strategy, says Immuta CEO Matt Carroll. Those regulations forced many organizations to reevaluate how they managed data across the entire enterprise in a way that now benefits their digital business transformation efforts, he notes.

Also read: Steps to Improving Your Data Architecture

Wrangling Data Management

The issues that organizations large and small are now encountering is the data that organizations are counting on to drive digital business transformation initiatives has historically not been especially well managed. There are a wide range of data quality issues that are, for example, now adversely impacting an organization’s ability to accurately train an artificial intelligence (AI) model. “Data management is the forgotten child of the AI era,” says Carroll.

It’s hard to say with absolute certainty when any organization will finally get around to addressing long-standing data management issues. It is fair to say, however, that those that don’t will find themselves unable to remain competitive against rivals that view data as a business asset that should be sweated as much as possible like any other business asset. Unfortunately, far too many organizations still view data as a cost to be minimized versus an actual investment opportunity to benefit the business.

Gaining Perspective on Data

The simple truth of the matter is most IT teams never had a lot of perspective on what data is of the most value to the business in the first place. Their job was to store and protect that data as best they could. All data was of relatively equal value. The business units that create the data know what data is important. They just don’t generally share that information with the IT teams tasked with managing it.

It should come as no surprise then to discover that five separate applications being employed by different business units within the same organization might not be synchronized with one another. Attempting to drive a digital customer experience relying on that data quickly becomes problematic when, for example, the applications used by the shipping department report  one thing and the applications employed by the finance team record something else.

These issues have been around for decades. The difference now is that organizations are discovering they can no longer be ignored as they find themselves being asked to deliver on some lofty promises that were made at the height of COVID-19 pandemic with little regard for actual everyday realities of IT.  

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