SAS, the leader in analytics, asked its experts in health care, retail, government, fraud, data ethics and more. "Curiosity helps businesses address critical challenges – from improving job satisfaction to creating more innovative workplaces. Curiosity will be the most sought-after job skill in 2022 because curious employees help improve overall retention, even during the Great Resignation." "The pandemic upended expected business trajectories and exposed weaknesses in machine learning systems dependent on historical data and reasonably predictable patterns. This identified an acute need to bolster investments in traditional analytics teams and techniques for rapid data discovery and hypothesizing. Synthetic data generation will play a major role in helping businesses respond to continued dynamic markets and uncertainty in 2022."

If there's been one overarching trend in analytics in 2020, it's been vendors' efforts to help organizations navigate the COVID-19 pandemic. Beginning in March when the novel coronavirus started its worldwide spread, analytics software vendors began developing general resources to inform both organizations involved in the fight against the spread of the virus and the general public. As the pandemic continued to grow, vendors began working directly with healthcare organizations and governments to build specific tools to help them make data-driven decisions related to COVID-19. But other analytics trends have either developed in 2020 or continued from previous years as well. Cloud migration continues to be significant, as does the development of augmented intelligence and machine learning features.

In 2019, enterprise demands rose for real-time and near real-time analytics, and data continued to expand its role in everyday business operations and decision-making. Enterprises will continue to build on these trends in 2020, and that will drive analytics vendors to add new capabilities and expand their offerings. Here are eight key trends for analytics in 2020. In-memory costs are decreasing, and this will drive more analytics to real-time environments. The demand for real-time or near real-time analytics will require fast CPUs and in-memory processing.

We've reached the third great wave of analytics, after semantic-layer business intelligence platforms in the 90s and data discovery in the 2000s. Augmented analytics platforms based on cloud technology and machine learning are breaking down the longest-standing barriers to analytics success. They bring insights to users rather than forcing users to unearth elusive trends, and provide more intuitive interfaces that make it easier to get the data people need to do their jobs. The historical line between operational applications and analytics continues to blur. Thanks to advances in machine learning, prescriptive "intelligent applications" have become a reality.

Data analytics are fast becoming the lifeblood of IT. Big data, machine learning, deep learning, data science -- the range of technologies and techniques for analyzing vast volumes of data is expanding at a rapid pace. To gain deep insights into customer behavior, systems performance, and new revenue opportunities, your data analytics strategy will benefit greatly from being on top of the latest data analytics trends. Here is a look at the data analytics technologies, techniques and strategies that are heating up and the once-hot data analytics trends that are beginning to cool. From business analysts to data scientists, everyone who works with data is being impacted by the data analytics revolution.