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Gartner: Organizations Will Shift From Big Data to Small and Wide Data

Gartner, Inc. predicts that by 2025, 70% of organizations will shift their focus from big to small and wide data, providing more context for analytics and making artificial intelligence (AI) less data hungry.

"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," said Jim Hare, Distinguished Research VP at Gartner. "In addition, decision making by humans and AI has become more complex and demanding, and overly reliant on data hungry deep learning approaches."

Gartner analysts discussed new data and analytics (D&A) techniques to build a resilient, adaptable and data literate organization during the Gartner Data & Analytics Summit 2021.

D&A leaders need to turn to new analytics techniques knows as "small data" and "wide data".

"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," said Hare.

Small and Wide Data Allow More Robust Analytics and AI

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.

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

Small and Wide Data Applications

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

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Gartner: Organizations Will Shift From Big Data to Small and Wide Data

Gartner, Inc. predicts that by 2025, 70% of organizations will shift their focus from big to small and wide data, providing more context for analytics and making artificial intelligence (AI) less data hungry.

"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," said Jim Hare, Distinguished Research VP at Gartner. "In addition, decision making by humans and AI has become more complex and demanding, and overly reliant on data hungry deep learning approaches."

Gartner analysts discussed new data and analytics (D&A) techniques to build a resilient, adaptable and data literate organization during the Gartner Data & Analytics Summit 2021.

D&A leaders need to turn to new analytics techniques knows as "small data" and "wide data".

"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," said Hare.

Small and Wide Data Allow More Robust Analytics and AI

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.

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

Small and Wide Data Applications

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

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Businesses that face downtime or outages risk financial and reputational damage, as well as reducing partner, shareholder, and customer trust. One of the major challenges that enterprises face is implementing a robust business continuity plan. What's the solution? The answer may lie in disaster recovery tactics such as truly immutable storage and regular disaster recovery testing ...

IT spending is expected to jump nearly 10% in 2025, and organizations are now facing pressure to manage costs without slowing down critical functions like observability. To meet the challenge, leaders are turning to smarter, more cost effective business strategies. Enter stage right: OpenTelemetry, the missing piece of the puzzle that is no longer just an option but rather a strategic advantage ...

Amidst the threat of cyberhacks and data breaches, companies install several security measures to keep their business safely afloat. These measures aim to protect businesses, employees, and crucial data. Yet, employees perceive them as burdensome. Frustrated with complex logins, slow access, and constant security checks, workers decide to completely bypass all security set-ups ...

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In the early days of the cloud revolution, business leaders perceived cloud services as a means of sidelining IT organizations. IT was too slow, too expensive, or incapable of supporting new technologies. With a team of developers, line of business managers could deploy new applications and services in the cloud. IT has been fighting to retake control ever since. Today, IT is back in the driver's seat, according to new research by Enterprise Management Associates (EMA) ...

In today's fast-paced and increasingly complex network environments, Network Operations Centers (NOCs) are the backbone of ensuring continuous uptime, smooth service delivery, and rapid issue resolution. However, the challenges faced by NOC teams are only growing. In a recent study, 78% state network complexity has grown significantly over the last few years while 84% regularly learn about network issues from users. It is imperative we adopt a new approach to managing today's network experiences ...

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