Why Big Data, IoT, AI and Cloud Are ConvergingKudzai
In Digital Transformation: Survive and Thrive in an Era of Mass Extinction, he argues that technology is at a inflection point and that the principle technology discussion in the digital workplace at the moment is how to manage the convergence of four megatrends: cloud computing, big data, artificial intelligence (AI) and Internet of Things (IoT). While these systems are making work more ‘intelligent’ they are also increasingly difficult to manage.
Convergence in the Workplace
The manufacturing industry, for example, has been working with these trends separately for years in a number of different ways and they are all starting to dovetail through the use of data. Here’s how each technology is working in the enterprise:
1. Cloud Computing
Software is now being offered as a service (i.e., cloud-based, where you are essentially leasing vs. purchasing it) for the past 10 years.
The IoT has allowed manufacturers to put sensors at the “edge” of their processes, so that they have much more data from many more areas within their operations to allow them to not only more quickly respond to downtime, but also predict when those events can occur.
3. Big Data
The IoT naturally generates “big data” so to deal with it, manufacturers now have options from vendors like Rockwell, Schneider Electric and others, or the analytics vendors like Tableau and Qlik that routinely deal with big data, albeit not primarily in a manufacturing or plant environment. With the analytical capabilities of big data, users can not only collect, but visualize and set up things like key performance indicators (KPIs) to monitor and respond to dips or out-of-limit processes.
4. Artificial Intelligence
For some vendors AI and machine learning (ML) go hand in hand, feeding vast amounts of data into an AI engine, and then applying context (meaning) to the data in order to understand patterns of behavior that can then lead to both good and bad events (downtime, out of spec processes).