The Future of Data Analytics in 2019

It has been two decades since the publication of the first paper cataloged in the Association for Computing Machinery (ACM) digital library to use the term "big data," and it feels as though the future of data analytics has been positioned since at least that time as the driving force behind the future of business on the whole. Even today, trends in data analytics are often predicted to spur innovation across numerous sectors and industries as greater quantities of data are collected and more and more professionals learn to assess it and use it to guide strategy.

Below, read about some of the top analytics trends in 2019, and see how they are helping all sorts of organizations and professionals stay competitive and ahead of the curve.

The term "Internet of Things" (IoT) has been trending for a number of years now, as data collection has become an increasingly ubiquitous function of a widening set of everyday objects. As wireless internet has become nearly universally adopted, more and more manufacturers have built connectivity into their devices, marketing it as a kind of convenience to consumers. Who wouldn't want their refrigerator to be able to tell them not only when they're running low on milk, but whether it's on sale at the grocery store this week? The "smart" devices that comprise the Internet of Things are so popular that some estimates predict that there will be more than 20 billion objects that can be classified as IoT in public circulation by 2020.

The payoff from IoT devices is not just for the consumer, however, but for manufacturers as well, in the form of the massive quantities of user data that are collected by connected devices. Manufacturers of consumer goods are becoming savvier every day at managing this data, using it to market new products to targeted consumers based on profiles of their behavior that can be interpreted from their data, and they will continue to explore new and more efficient ways to do so in the coming years.

While the mere collection of data may have been an impressive feat in yesterday's business world, companies have learned that data is only as good as the uses to which it can be put. The future of analytics, then, is not just about increasingly complex ways of collecting and managing data, but conversely, about making it easy to interpret and act upon by all kinds of employees.

One increasingly common way in which companies are helping make data more immediately actionable is through "embedded analytics." This refers to the integration of analytics data into platforms that are used for other purposes, by employees whose main function is not an analytics one. When organizations embed analytics in customer relationship management software like Salesforce, for instance, they are helping members of their marketing team gauge the efficiency of their efforts in real time and develop effective strategy at a much more rapid pace.

Companies are coming under increasing scrutiny for mishandling of data. In 2018 alone, the Information Commissioner's Office (ICO) issued more than $3 million in fines for data-related offenses to companies that include Uber, Equifax, and Facebook. As companies come to appreciate the growing influence of compliance-related oversight, you can expect to see more standardization across data collection practices to stay in line with increasingly specific regulations.

And even beyond strict legal compliance, ethical collection and management is one of the most rapidly accelerating trends in data analytics today. The public has demonstrated an inclination to voice their opinions about companies' less-than-ethical behavior with their actions and their dollars, and smart businesses will try to get out in front of any concerns about their handling of customer information.

Trends in data analytics have tended to coalesce around key concepts or technological developments over the last several decades. While cloud storage and artificial intelligence have both progressed from pipe dreams to increasingly complex, functional and ubiquitous parts of our everyday lives, many experts predict that the next frontier in analytics is deriving useful data from voice technology.

People the world over have become accustomed to issuing voice commands to Siri, Alexa and any number of other virtual assistants, and technology consultancy Juniper Research projects that use of smart assistants will expand by 1,000 percent in the next five years.4 To accommodate this shift, producers of voice-enabled devices will turn to machine learning to develop more precise and effective algorithms for translating your vocal commands into the data that allows your device to give you what you asked for.

If it hasn't already been clear for years, "big data" is no longer just the purview of companies in the technology sector. Every industry is impacted by the evolution of analytics, and the future of data analytics is one in which decisions at all levels of all organizations will likely be guided by data in some fashion.

One contemporary example is the agricultural sector. While farming may seem as far afield from data collection technology as you can imagine, the industry has seen analytics usage skyrocket in recent years. Data collection and analysis are being used to calculate fertilizer needs, plot efficient crop-spraying schedules, measure soil chemistry and more. An efficient and fully functional agricultural sector is key to feeding a growing world population, and smart farms of all sizes are doing their part to help.

The Online Master of Science in Business Analytics (MSBA) from the Raymond A. Mason School of Business is designed to help you master the most up-to-date technical analytics skills and apply them confidently and intelligently in a business leadership role. Hear from Online MSBA Faculty Director Joe Wilck how our innovative program has been designed to sharpen your competitive edge, and apply today to stay one step ahead of trends in data analytics in 2019 and into the future.