Gartner Identifies Top Data and Analytics Trends for 2021

Published On: March 29, 2021Categories: Buzz, Uncategorized

Gartner has identified the top data and analytics (D&A) technology trends for 2021 that can help organizations respond to change, uncertainty and the opportunities they bring in the next year.

“The speed at which the COVID-19 pandemic disrupted organizations has forced D&A leaders to have tools and processes in place to identify key technology trends and prioritize those with the biggest potential impact on their competitive advantage,” said Rita Sallam, distinguished research vice president at Gartner.

Among the top trends, the greater impact of artificial intelligence (AI) and machine learning (ML) requires businesses to apply new techniques for smarter, less data-hungry, ethically responsible and more resilient AI solutions. By deploying smarter, more responsible, scalable AI, organizations will leverage learning algorithms and interpretable systems into shorter time to value and higher business impact.

The second trend suggests that open, containerized analytics architectures make analytics capabilities more composable. Composable data and analytics leverages components from multiple data, analytics and AI solutions to rapidly build flexible and user-friendly intelligent applications that help D&A leaders connect insights to actions.

According to the next trend, increased digitization and more emancipated consumers are causing D&A leaders to increasingly use data fabric to help address higher levels of diversity, distribution, scale and complexity in their organizations’ data assets. Fabric uses analytics to constantly monitor data pipelines. A data fabric utilizes continuous analytics of data assets to support the design, deployment and utilization of diverse data to reduce time for integration by 30%, deployment by 30% and maintenance by 70%.

Gartner also says that the extreme business changes from the COVID-19 pandemic caused ML and AI models based on large amounts of historical data to become less relevant. At the same time, decision making by humans and AI are more complex and demanding, requiring D&A leaders to have a greater variety of data for better situational awareness. As a result, D&A leaders should choose analytical techniques that can use available data more effectively. D&A leaders rely on wide data that enables the analysis and synergy of a variety of small and large, unstructured, and structured data sources, as well as small data which is the application of analytical techniques that require less data but still offer useful insights.

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The trends can help companies respond to change, uncertainty, and opportunities when properly leveraged.

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