As vaccines start to rollout for the coronavirus, the proverbial light at the end of the COVID-19 tunnel is finally within view. As the entire business world was flipped on its head due to regulations set in place due to the pandemic, innovation was in no short supply as companies scrambled to adjust with the times. Everything has silver linings, and one of the ones that came with COVID-19 was a lot of evolution in how business is conducted, especially regarding remote workspaces.
“Data Science and machine learning is revolutionizing every organization, business and even our private lives.” says Margrét V. Bjarnadóttir, Ph.D., Assistant Professor of Management Science and Statistics in the online MBA program at the University of Maryland. Secure sharing of data was a new challenge that companies faced due to the nature of remote work, as were other aspects of data collection and analyzation. Some trends from the remote work surge are expected to stay, some are not, and other technological advances are also going to mold the data analytics trends expected in 2021.
Here is a look at the top 5.
According to Anirudh Ruhil, Ph.D.Director of the Voinovich School of Leadership and Public Affairs at Ohio University, “the bulk of analytics will start operating in the cloud…”
The cloud, and security surrounding it, wasn’t originally built with analytics and analytics sharing in mind, but with a little boost from the necessity of COVID, faster networks and data services are allowing for cloud evolution ultimately allowing for real-time analytics.
“Cloud based data systems,” explains Andrea Yoder Clark, Professor in MS Business Analytics Program at the University of San Diego School of Business, “make storing and accessing large amounts of historical data less expensive and easier.” This not only makes current relationships easier, but it also opens up possibilities for consultation, and even remote hiring, from all around the world.
She adds, this shift in perspective allows companies to quickly understand if their organizations’ point in time metrics are typical or if they are deviating from an established baseline. Similarly, dashboarding and reporting styles are shifting from point in time KPI metrics, to metrics that are displayed in the context of historical performance and enable root cause analysis in the dashboard itself vs. relying on an analyst to follow-up and explain.
The digital revolution has done a lot for business, but it might have done even more for consumers. Though analytics verbiage may not be household, the ability to understand data is becoming easier and easier thanks to programs created to do just that. Things like health data and financial analytics are now viewable online by consumers who formerly would have had to contact their doctor or advisor for information.
“Clinical data integration across multiple healthcare sectors is ripe for innovative disruption and will inevitably play a role in new developments,” says Jacob Krive, PhD is a Clinical Associate Professor for the Online Master of Science in Health Informatics at the University of Illinois, Chicago.
He adds, technologies supporting real world evidence (RWE), remote real-time patient monitoring as an enhancement to traditional home care services, incorporating genetic and other personalized medicine data into clinical practice, and telehealth will take advantage of the expanded opportunities to incorporate data from multiple primary sources and combine in search of new solutions and health outcomes.
About a five years ago, the average college graduate had spent his or her entire life with a mobile phone in their pocket. In the next few years, a baseline understanding of data analytics will also come with every new hire who is fresh off of a traditional college career. This generation has been subjected to data analytics in every part of their lives, from school, to exercise, and even with sleep patterns. There will be an acceleration in the quantification of human activities: productivity at work, exercise, metabolism, diet, social media use at work, energy usage, etc. The tools are here, they only need to be adopted more widely.
Taking this knowledge to the workplace sets the next generation apart from previous ones, as “opportunities for new business models built on machine and deep learning on the generated data” continue to become more prevalent, according to Wallace Chipidza is an assistant professor in the online Master of Science in Information Systems & Technology program at Claremont Graduate University.
Smart contracts also made a surge in 2020, even before the COVID restrictions, and are expected to become a new normal in data storage. The security of blockchain transactions is what most point to when giving it praise, but it also offers transparency in those transactions, adding to the trend of consumer control.
In an evolving word, where blockchain has several uses from health record management to supply chain information organization, this technology is poised to be hugely important once again in 2021.
More Trust in AI
Predictive analytics and machine learning are both widely used in the data world, but not necessarily widely trusted. As they both continue to prove to be valuable and evolving ways to save time and money, more decision makers are putting their trust in AI. For those with positions within data analytics, it may be a wise decision to further educate yourself on how to utilize these technologies.
AI has already been used in classrooms, hospitals, and in workplaces, and 2021 should expect an ongoing surge in AI developments.