Data Management Fundamentals are the First Step Towards Advanced Data Practices, New CompTIA Report Reveals

AI Guide for Businesses Created by CompTIA Artificial Intelligence Advisory Council

Companies eager to maximize the value of their digital data are taking small steps to establish the strong foundational policies and practices needed for managing data, a new report published by CompTIA, the leading trade association for the global information technology (IT) industry, finds.

Three areas of activity are emerging, according to the CompTIA report “Trends in Data Management.”

First, companies are evaluating the sources of their data, how it flows through the organization and how often it is processed for analysis. Next, companies are structuring data management teams of in-house staff, third-party providers of data services or a combination of the two. Finally, some organizations are evaluating how blockchain, other digital ledger technologies or data-driven artificial intelligence may fit in.

“For many organizations data management has only recently become a priority,” said Seth Robinson, senior director of technology analysis at CompTIA. “So while there is much work to be done, they are unencumbered by legacy thinking and can begin with a blank slate.”

The number of companies that feel they are exactly where they want to be with their data capabilities has taken a step backward, according to the report. One in four respondents said their company is exactly where they want to be today with their data capabilities. That’s down from 31% in a 2015 survey. Another 41% said they are very close today, up marginally from 2015 (38%).

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Digital Ledger Technology

One of the innovations that’s slowly beginning to take hold is the use of blockchain or other digital ledger technologies (DLT) as data structures.

In the CompTIA survey 21% of companies said they’re developing tools that use DLT as an underlying technology, while 27% have purchased tools that use DLT. Among the applications companies are exploring are digital identity, smart contracts, distributed storage, regulatory compliance, asset management and cryptocurrency and payments.

“While these results are likely skewed due to early lack of understanding around the technology, there is clearly high interest and potential for DLT solutions,” Robinson said.

The top challenge companies expect to face when it comes to DLT solutions include a lack of skill in working with and knowledge about the technology; uncertainty over the benefits and use cases for the technology; and a lack of buy-in from other companies, which is a necessity to realize the true value of DLT.

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Building Strong Data Practices

As businesses look to build out their data practices Robinson recommends that they focus on four areas.

  • Data Sourcing to understand where data is coming from and ensure that it is “clean” and of high quality.
  • Data Processing to assure that different types of data are processed, stored and integrated appropriately.
  • Data Analytics to tie data to corporate objectives and present findings in a way that business leaders will understand.
  • Data Security to ensure integrity and minimize risks from data loss or breaches.

These areas are relevant to current operations and, more importantly, as companies make use of emerging technologies and trends to support their advanced data management efforts.

Robinson compared the so far modest embrace of data management to the practices companies once used with cybersecurity.

“For some time ‘good enough’ was as far as many companies were willing to go with their cybersecurity investments and activities,” he explained. “They soon learned that stance was not nearly good enough and cybersecurity was elevated from an IT function to a business priority. We may see the same trajectory when it comes to comprehensive data management.”

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