This article is more than 1 year old

User-built low-code apps tipped to dominate analytics by 2025

Analysts also insist organizations need to get data ops for AI in gear or face 2-year delay

By 2025, half of analytics will be developed by business users via a low-code or no-code modular assembly experience, according to Gartner.

Presenting its vision for trends in data and analytics, the global analyst said the future would put business users, rather than IT or data engineering, in the driving seat, at least in terms of applications.

Augmented capabilities ... can be proactive in ensuring it isn't biased, and focusing heavily on that idea of data diversity

Carlie Idoine, veep and analyst, told London's Gartner Data & Analytics Summit that analytics would be based around "automated data stories" created by business users.

"How can we start a story? What happened? How do we talk about why did it happen? And then if I know that, what will happen next? To do this, we have to move from the static IT embedded applications to more business composed data and analytics," she said.

Idoine said it would be "business technologists" leading the adoption of the approach within organizations.

"It's what we historically have called the citizen. It's people in the business that are using data and analytics to actually make the business decisions," she said.

These business people would expect access to contextual data outside business numbers. "Think video documents, think [web]logs: all of this data that comes together to give us more context for the analysis that we want to do. Context-enriched analytics is the direction that we're going to think beyond the traditional approach. How can we leverage more data and not only more data, but different kinds of data?"

Meanwhile, tech and data engineering teams will be expected to create data pipelines for AI — which Gartner predicts to be omnipresent — with data that guards against bias and represents diversity in society.

Organizations which do not have a sustainable plan to "operationalize" the way they manage data and analytics by 2024 face a two-year setback to their efforts, according to Gartner.

Ted Friedman, distinguished veep and analyst at Gartner, said: "Without the right data and the right data capabilities underneath AI systems probably are going to be faulty, possibly even dangerous. And we observed that many organizations aren't in the right place in terms of their data management capabilities required to support the deployment of AI."

He said making data management ready for AI would not mean businesses would have to throw away their existing data management systems. "You have things like data integration capabilities, data quality assurance, and data governance capabilities: they are still very much required.

"But we now need to extend data management and bring in some new thinking in terms of synthetic data, augmented capabilities that can be proactive in ensuring it isn't biased and focusing heavily on that idea of data diversity."

Friedman said Gartner's vision of data and analytics was set against the backdrop of global economic, geopolitical, social and medical uncertainties.

"This chaos and uncertainty that shapes the backdrop against which we organize our top trends," he said.

Whether or not IT departments agree with Gartner's visions is a moot point. But they might want to be aware of them next time they talk to the senior management team, who may well have a hotline to the global tech soothsayer. ®

More about

More about

More about


Send us news

Other stories you might like