Regardless of the size of a business, data management across the enterprise has always presented unique challenges, combined with the complexities of making the right data available at the right time. When you add social, mobile, analytics and cloud technologies into the mix, many of the more traditional data management techniques and technologies simply cannot keep pace. Companies are now looking for agility, speed, new types of fast-growing data and innovative ways of working and transacting.
According to all the analysis from many marketing and research firms, the number of Internet-connected devices will explode over the next five years. By 2020, we can expect to see well over twenty billion devices ranging from complex interactive systems to tiny sensors. All of these will be collecting and transmitting data over the Internet.
The amount of data predicted that will be generated by the Internet of things (IoT) will be beyond measure, at this point. A recent ABI Research (News - Alert) report estimates that we will see an average growth rate of 20 percent per year until 2020.
If organizations want to keep pace, they will have to figure out how to implement IoT projects and radically rethink about the way they transmit, store, manage and exploit the data that is produced. Lines are beginning to blur, where there once was a separation of manufacturing operations technology (OT) and enterprise information technology (IT) systems, the IoT seems to now be creating a convergence of the two into a network architecture that is unified.
As you can see, one thing leads to another, creating the potential for data overload. The potential that the IoT will offer in terms of data is expected to be massive. In turn, it will enable organizations to develop deeper and timely insight from the volume of data that it will generate. This in turn, will present organizations with the challenge of finding the steps needed in order to derive new insight from big data.
“Compared to the general-purpose conventional networks, industrial networks are characterized by a large variety of technologies and communication protocols, whose combination is determined by the requirements of the specific application they address,” said Eugenio Pasqua, research analyst at ABI Research. “As a consequence, there is typically little interoperability with conventional networks, but also between different industrial networks. Sharing data among different facilities or with the higher levels of an enterprise remains a very challenging task within this context.”
As we see the IoT connect more devices, and as machine-to-machine (M2M) communications continue to offer more valuable data, if the challenge to deal with it is not met, the data becomes a useless mass of wasted space. We will see more smart devices, which will connect even more devices and each produce its own data set. The IoT is establishing its presence and is being felt in data management as well, and it remains to be seen how the challenge will be met.