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Small and wide data to power analytics and AI, Gartner finds
Thu, 20th May 2021
FYI, this story is more than a year old

By 2025, 70% of organisations will shift focus from big to small and wide data, according to analysts at Gartner.

This, in turn, will provide more context for analytics and make artificial intelligence (AI) less data hungry, Gartner states.

Gartner distinguished research vice president Jim Hare says, “Disruptions such as the COVID-19 pandemic is causing historical data that reflects past conditions to quickly become obsolete, which is breaking many production AI and machine learning (ML) models.

"In addition, decision making by humans and AI has become more complex and demanding, and overly reliant on data hungry deep learning approaches.

D-A leaders need to turn to new analytics techniques knows as 'small data' and 'wide data', according to Gartner.

Hare says, “Taken together they are capable of using available data more effectively, either by reducing the required volume or by extracting more value from unstructured, diverse data sources."

Small data is an approach that requires less data but still offers useful insights. The approach includes certain time-series analysis techniques or few-shot learning, synthetic data, or self-supervised learning.

Wide data enables the analysis and synergy of a variety of small and large, unstructured, and structured data sources. It applies X analytics, with X standing for finding links between data sources, as well as for a diversity of data formats.

These formats include tabular, text, image, video, audio, voice, temperature, or even smell and vibration.

Hare says, “Both approaches facilitate more robust analytics and AI, reducing an organisation's dependency on big data and enabling a richer, more complete situational awareness or 360-degree view.

"D-A leaders apply both techniques to address challenges such as low availability of training data or developing more robust models by using a wider variety of data.

Potential areas where small and wide data can be used are demand forecasting in retail, real-time behavioural and emotional intelligence in customer service applied to hyper-personalisation, and customer experience improvement.

Other areas include physical security or fraud detection and adaptive autonomous systems, such as robots, which constantly learn by the analysis of correlations in time and space of events in different sensory channels.

Small and wide data will be discussed during the virtual Gartner Data - Analytics Summit for APAC in June. Other top trends that will be discussed include digital ethics, graph analytics, responsible AI, DataOps and data fabric. There will be presentations from Macquarie Bank, NSW Department of Customer Service and other ANZ organisations.