Where does your enterprise stand on the AI adoption curve? Take our AI survey to find out. This post is by Dr. Mukta Paliwal, senior data scientist at Persistent Systems. As many as 50% of Gartner client inquiries on the topic of artificial intelligence involve a discussion involving the use of graph technology, the market research firm said in its Top 10 Data and Analytics Trends for 2021. Every large enterprise wants to exploit available data to bring more insights for doing business at scale.

When COVID-19 hit, organizations using traditional analytics techniques that rely heavily on large amounts of historical data realized one important thing: Many of these models are no longer relevant. Essentially, the pandemic changed everything, rendering a lot of data useless. In turn, forward-looking data and analytics teams are pivoting from traditional AI techniques relying on "big" data to a class of analytics that requires less, or "small" and more varied. Transitioning from big data to small and wide data is one of the Gartner top data and analytics trends for 2021. These trends represent business, market and technology dynamics that data and analytics leaders cannot afford to ignore.

When COVID-19 hit, organizations using traditional analytics techniques that rely heavily on large amounts of historical data realized one important thing: Many of these models are no longer relevant. Essentially, the pandemic changed everything, rendering a lot of data useless. In turn, forward-looking data and analytics teams are pivoting from traditional AI techniques relying on "big" data to a class of analytics that requires less, or "small" and more varied. Transitioning from big data to small and wide data is one of the Gartner top data and analytics trends for 2021. These trends represent business, market and technology dynamics that data and analytics leaders cannot afford to ignore.

Traditionally, banks targeted older customers for wealth management services, assuming that this age group would be the most interested. Using augmented analytics, banks found that younger clients (aged 20 to 35) are actually more likely to transition into wealth management -- a clear example of how relying on business users to find patterns, and on data scientists to build models manually, may result in bias and incorrect conclusions. Augmented analytics is just one of the top 10 technologies Gartner has identified with the potential to address these and other major data and analytics challenges in the next three to five years. Digital transformation has put data at the center of every organization. Businesses are awash with data.