According to a recent LinkedIn post from Quest Software, internal research conducted with analyst firm Omdia suggests that data teams spend about 81% of their time duplicating data work. The post argues that this inefficiency is increasingly problematic as enterprises seek to deploy AI systems that require rapid, trustworthy, and reusable data assets.
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The company’s LinkedIn post highlights a shift toward treating reusable data products, supported by automation and governance, as a way to reduce rework and accelerate analytics. It cites survey findings that such approaches are associated with faster time-to-insight, improved data accuracy, and better revenue attribution for roughly 74% of teams.
As shared in the post, Quest Software positions its automated data product delivery capabilities as a response to this demand, with its VP of Product providing further analysis in an accompanying blog. For investors, the emphasis on automation, AI-ready data, and measurable business outcomes signals a focus on higher-value data management offerings, which could strengthen the company’s competitive standing in the data and analytics infrastructure market.
If adoption of data products grows as implied, vendors that streamline governance and reuse may capture increased enterprise spending tied to AI initiatives. Quest Software’s collaboration with Omdia and promotion of research-driven insights may also support its marketing and sales efforts with large organizations seeking to quantify return on data infrastructure investments.