AI drives data analytics surge, study finds

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Enterprise managers have an insatiable need for better analysis of more data, and the epidemic has only intensified the search. That is in the findings of a recent report by analyst Pay Firm 451 Research.

“Trends in Data, AI and Analytics, 2021” surveyed a wide range of enterprise IT outlets and found that many people are increasing their investment in data collection and generating better analytics. As a result, AI Analytics is bringing new life to data analytics tooling.

In many cases, the new analysis relies on the deployment of artificial intelligence and machine learning algorithms to find the right signal or trend.

Was this shift the result of COVID? Companies in the survey were basically divided on the question, with 51% agreeing that “my organization has increased the number or scope of active analytics projects as a result of COVID-19.”

This shift reversed a trend characterized by 451 researches in the early months of the epidemic. When lockdowns and other measures began, many companies halted new projects, and data-based analyzes were an easy target. As projects have resumed, significant changes are taking place.

“The unprecedented level of change we’ve seen means that historical data and models are no longer relevant,” the 451 research series suggested in a survey from 2020 onwards.

How have things changed? For many, the increase in remote work means more opportunities to track and measure. The report suggests that this leads to more options for analytics that are clearly driven by the need to understand how to deploy resources in a new business environment and how to meet customer needs.

Data analytics varies with business models

Between employees working from home, widely distributed office space and the demand for more digital services, analytics can help decision makers understand which parts of the business are working and which are not.

Most of this is part of a trend that has been unfolding long before the epidemic and will remain independent of it. The report found that many surveys expect broad growth in all analytical options, from traditional business report generators to self-service business intelligence / visualization tools.

The highest growth was seen in automated business metrics / event detection and alerting tools, which give field managers a way to track key metrics for dangerous changes.

“The prevailing view in the field of data and analytics is that there is another wave of analysis tools associated with traditional forms of business intelligence, especially reports and dashboards generated by IT and data analysts, as well as self-service business intelligence / visualization tools. On the vine, ”the report noted. But 451 research clearly adds that survey data “tells a different story” and that such tools do not dry up.

Indeed, more and more tools are being used, the report concludes, as AI and what the report calls “aging intelligence” is becoming a common part of business intelligence and reporting. For example, 25% / are now using automated business metric event detection and alerting tools, but 39% are expected to use it in the next two years. In general, automated instructions and other heavy process analysis will form the basis for more dashboards and other business intelligence.

Covid gives birth to data culture

The report also explores how epidemics can change what companies call a “data culture”. Many survey data have reported investments in new products and tools to simplify data analysis and reduce sealing.

The data storage facilities that will take the form, however, are an active area of ​​experimentation and investment. The report notes that new capabilities and new products are blurring the lines between concepts such as Data Lake and Data Warehouse. Product lines are coming together as vendors of special offers add similar features.

“Establishing a comprehensive data culture requires more than just technology investment. While data management is at the forefront of organizations ’reporting efforts to support investment data culture, the broader challenge is one of change management.

It applies to change from the epidemic and whatever is to come next.


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