Working with a large amount of data that is not only fast but also diverse in its forms is described as Big Data. The term "Big Data" may not be as well-known as it was a few years ago, but that's only because many of the concepts it encompasses have become deeply ingrained in our culture. However, most organizations are still having difficulty extracting value from most of the data they have access to. It's still very much in its infancy as a business activity.
Here are some of the key trends influencing big data and analytics:
Cloud computing has a significant impact on the way big data analytics work. The ability to access large data sets and act on real-time data without requiring costly on-premises equipment has fueled the growth of apps and businesses that provide on-demand data-driven services.
Another major trend that will affect the impact of Big Data and analytics in our lives in the coming year is edge computing. This refers to equipment that are designed to process data on-site rather than transferring it to the cloud for storage and analysis. Some data just needs to be acted on too quickly to risk it being sent back and forth - a good example is data collected from sensors on autonomous vehicles.
Artificial intelligence (AI)
Analytics has been transformed by artificial intelligence (AI). With so much structured and unstructured data generated by businesses and their consumers, even automated manual analytics can only scratch the surface of what's available. Machines—computers and software—that are capable of learning for themselves are the easiest way to think of AI as it is utilized today.
Before taking any action based on the findings, data visualization is the "last mile" of the analytics process. Graphs, charts, and dashboards have traditionally been used to communicate between machines and humans, highlighting key discoveries and assisting in determining what the data suggests needs to be done.