What is digital transformation without a solid data foundation? While digital transformation is everywhere—and is seen as an essential strategy for staying ahead of the competition —it requires effectively leveraging data assets and competing on analytics. Competing on data analytics is now an essential element of digital transformation, and this requires that data managers and their business counterparts successfully capture and rein in the data flowing through and around their enterprises. It means greater care and attention need to be applied to data management and provisioning, especially information about customers, partners, and suppliers. Data is also flowing in from a wide range of sources, such as the Internet of Things, artificial intelligence systems, mobile devices, social media, and production systems.
Competing on data analytics successfully means building well-honed insights out of chaos. It means elevating the roles of data managers to provide essential guidance and leadership as enterprises transform. Organizations need the agility and insights that well-managed and deployed data can bring. In a recent survey of more than 220 data scientists and IT members, fielded among the membership of the Quest IOUG Database & Technology Community, we looked at how data management is affecting modernization within their organizations.
While database automation and practices such as DataOps and AIOps have been surging, this has not provided relief for data teams tending to day-to-day tasks. In this most recent survey, 43% of data managers say the amount of resources spent on ongoing database management is severely limiting their competitiveness—an increase of 65% over the 2020 survey.
It is notable as well that a total of 86% agree that to some degree, their administrative tasks have become an inhibitor to corporate growth. (see Figure 1)
A number of mundane administrative tasks continue to consume a significant part of data management budgets. Maintaining system stability—patching, fixing, and upgrading— is considered the costliest part of data managers’ jobs, according to close to half (49%). In addition, 40% indicate much of their time and budget goes to ensuring security, while 36% see significant portions of their time and budgets dedicated to testing and quality assurance (see Figure 2).
Data managers aren’t taking the surge in administrative tasks sitting down, of course. The leading strategy being undertaken to mitigate time devoted to administrative overhead is the consolidation of databases and data centers, which is occurring at 33% of respondents’ sites. Close to one-third, 31%, are also pursuing approaches that virtualize or abstract data environments, including virtualization and cloud. Specific cloud based strategies are the adoption of platform-as-a-service (25%), infrastructure-as-a-service (24%), and database-as-a-service (22%) solutions (see Figure 3).
Another 29% are looking to their major vendor—in this case, Oracle—to help better automate and provide greater ease of use. However, database automation ranks relatively low as a strategy at this point, with only 15% of respondents opting for tools to deliver such capabilities.
Part of the role of data managers is to oversee the regular updating or upgrading of their environments to incorporate new features and greater security. However, keeping up with database upgrades take time, the survey shows. A majority of data managers, 55%, report that they anticipate periods of six months or more after a major release until they begin the upgrade process.
Explore these and other findings in the recently released Managing Data in a Demanding Digital Economy
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