dbt Labs, the leader in standards for AI-ready structured data, has officially published the results from its Analyst Revolution report, which would be a comprehensive study focused on uncovering costly inefficiencies and opportunities to maximize productivity across enterprise data analysts.
Going by the available details, this particular report was developed in close collaboration with The Harris Poll. More on the same would reveal how it reveals that organizations are losing 9.1 hours per analyst each week to inefficient workflows, totaling upto $21,613 per employee annually from a monetary standpoint.
Beyond that, the findings also reveal how organizations can seamlessly build a competitive advantage, transform analyst roles, and drive impact through investing in governed, AI-powered self-serve platforms.
“The number of professionals working around governance systems is alarming, but it’s a clear sign for leaders that data teams need better technology that enables them to streamline and accelerate their work,” said Libby Rodney, Chief Strategy Officer at The Harris Poll. “The onus is now on leaders to implement solutions that will reduce friction and boost agility.”
Talk about the given report on a slightly deeper level, we begin from a piece of discovery which claims that analysts spend, on an average, no more than 22% of their day generating insights, with the remaining 78% taken up by data preparation, validation, tool navigation, and other tasks.
As for why that is the case, 62% report feeling overwhelmed by the number of tools required to do their jobs. The average analyst essentially uses 5.4 platforms daily and switches between tools nearly six times per day, causing 65% of professionals to experience burnout.
Next up, the survey discovered most (89%) analysts have experienced limitations in available data tools or data access, driving many to use unapproved tools. You see, well over half (54%) admit to using AI tools like ChatGPT to analyze company data outside of approved systems, while 40% use personal API keys or free online tools to process organizational data.
In case that wasn’t bad enough, 32% also admit to creating workarounds for bypass governance processes entirely, and an equal number use personal software or tools not approved by IT. Having said so, there remains an awareness regarding the detrimental nature of this approach, as 63% reported that working outside governed systems actually delays their projects and requires retroactive validation.
“As our data needs evolve, empowering analysts with seamless self-exploration becomes increasingly critical,” said William Tsu, Senior Analytics Engineer at WHOOP. “dbt’s new analyst offerings enhance discoverability and enable faster, more intuitive, and governed self-service.”
Another detail uncovered by dbt’s survey relates to how 72% of data analysts report their organization isn’t investing enough in AI-powered platforms, but at the same time, 90% agree they desperately need more efficient tools to meet business demands.
The said 90% lot plans on integrating more AI tools to support tasks like real-time data quality detection (42%) and automated visualization (40%). In fact, AI-powered task automation ranks as the single most valuable platform feature on analysts’ wish lists.
Moving on, an estimated 93% of analysts were found to believe an all-in-one platform would increase their productivity, whereas on the other hand, almost all analysts surveyed (96%) were deemed as more likely to stay with employers who invest in workflow optimization. Against that, 85% said they would consider leaving employers who use outdated tools.
Among other things, it ought to be acknowledged that this particular survey took into account the opinion of more than 510 data analysts, business analysts, quantitative analysts, data specialists, and data scientists working across sectors like Finance, Healthcare/Pharma, and, CPG/Retail etc
Making this development even more important would be the fact that more than 80,000 data teams use dbt, including those at Siemens, Roche and Condé Nast, to support their operations.
“It’s clear that analysts want to work with data in a way that makes them more productive, but also more fulfilled at work,” said Mark Porter, CTO of dbt Labs. “Today’s analysts are drowning in manual, labor-intensive tasks and can be bottlenecked by engineering counterparts. The companies that provide unified platforms will create a symbiotic relationship where AI reduces time-consuming work and frees analysts to deliver the strategic insights.”
