How quickly are data trends evolving, and how will they affect us in the near future? The long and short of it is the wide world of data is fast on the move. Here are six incredible data trends that will soon make an impact on all of us, if they haven’t already in one form or another.
The Internet of Things (IoT)
One data-driven innovation that’s visibly taken the tech world by storm is the IoT—the network of smart, intercommunicating physical objects now connected to the Internet. These objects comprise everything from appliances and medical devices to industrial machines and transportation vehicles that take advantage of sensors, software, and internet connectivity to serve various purposes. As you can imagine, these objects generate large volumes of data to perform complex tasks that you’d normally associate more with traditional computing devices.
Real-time predictive analytics
Many organizations are now dabbling with more predictive data management strategies as opposed to reactive ones. The mindset of predictive analytics, as you can guess, is to predict actions or emergent problems before they even occur, and this is made possible by performing data analytics in real-time. Today, real-time predictive analytics is beginning to play a big role in the online and in-store marketing space, as this methodology of analysis reveals vital information that can positively impact the customer acquisition or customer relationship endeavors of a business.
One of the best use cases for this technology is in improving the in-store shopping experiences of customers. Backed by geofence and beacon technologies that can communicate with the shoppers’ smart devices, predictive analytics solutions can obtain information about these customers’ behavior in real-time, allowing the retailer to send personalized marketing messaging, offers, and coupons at exactly the right moment.
Artificial Intelligence (AI) and machine learning
AI is no longer the stuff of science fiction. In fact, the machine learning field of AI is currently on the rise. Machine learning enables computing devices to “learn” new things without being explicitly programmed and to independently analyze caches of big data. In detecting fraud and other financial crimes, for example, financial organizations can use software that uses machine learning to continually train itself when it comes to detecting outlier transactions and suspicious customer behaviors. This way, criminals can be caught right when they are committing the actual crime, and often, even before they actually do.
Beyond the cloud or the data center, high-level computing processes can now be done at the “edge,” or closer to the source of data generation (i.e., the IoT devices and sensors). Edge computing frees up storage space in the cloud, and thus lessens costs for cloud maintenance, while at the same time making use of data analysis capacities from sensors and embedded devices.
It’s not only edge computing that will change up the way we handle large, disparate volumes of data—soon enough, we’ll hit the pinnacle and golden age of quantum computing as well. Quantum computing, which will benefit from the way energy and matter works on a subatomic level, will result in computing performance gains that is unimaginable at the level of even the most powerful computers today.
Suffice it to say that we’re close to the renaissance of Big Data—and this will shape the future of technology in the same way data revolutions of the past have influenced the present.