Companies and individuals are becoming more at home with big data and data analytics. As advanced analytics services become increasingly commonplace and applications become more widespread, new tools and trends are emerging. Here are some exciting technological developments in the field of data analytics that are likely to take hold this year.
Machine learning and artificial intelligence
Machine learning is becoming more common and more sophisticated, but applications so far have been limited. This is likely to change in 2017, with greater volumes of data available and the technology being applied to a much wider range of situations. Many areas that already use data analytics can benefit from machine learning, including custom recommendations for consumers or predictions on how a new product will be received. Machine learning can also be used in applications such as…
There are many ways in which artificial intelligence can be used in apps to improve user experiences and provide better results. Functions like natural-language processing and neural networks can allow apps to do things like respond to complex requests or prioritize emails and tasks. Gartner expects that by 2018, most of the world’s 200 largest companies will be making use of intelligent apps in some way.
Chatbots are already used to some extent, but 2017 promises to see their role expand in many areas. These bots can do things like provide customer support and perform basic functions on command. They can also be used to help deal with immense volumes of data. The amount of data collected and stored is constantly increasing, and much of it is unstructured and therefore not being used to its full potential. Intelligent bots can uncover and communicate information from this data that would otherwise be difficult to discover.
As data analysis becomes more sophisticated and people become more creative in applying it, task automation will increase. Workers spend a lot of time doing straightforward, repetitive tasks, and programs can be created to reduce or eliminate those. This will free up employees to spend more time on complex work that cannot be handled by a computer.
Prescriptive applications over predictive ones
Companies have long been taking advantage of analytics to predict what might happen in the future — how people will behave, how well a particular product will sell, or how much a market will grow or shrink over the next few years. However, prescriptive analytics is beginning to pick up steam, and will likely be much more widely adopted in 2017.
Rather than estimating how something might perform, prescriptive analytics looks at many factors and many objects to recommend the best course of action. With this tool, for example, it is possible to test several product launches before choosing one, or determine what marketing initiative will have the best chance of success. This reduces risk and makes it much more cost-effective to test and evaluate multiple options.
New and stronger data security
With so many new ways of integrating data into work processes and everyday life, data security will also evolve. The Internet of Things is growing, and has been shown to have weaknesses that need to be addressed. Organizations are also collecting, transferring, and analyzing greater amounts of data than ever before, necessitating stronger and more flexible security. 2017 will bring innovations and improvements as security teams work to keep up with new data technology.