In the past few years, IoT has grown from a set of cutting edge technologies to a situation where almost everything from automobiles to household items are connected. Different researchers and technology companies such as Cisco have estimated that by the end of 2020, the world might see up to 50 billion devices connected. The world might even get to a point where devices that lack IoT capabilities get too expensive since manufacturers cannot harvest any data from them. This data makes the Internet of Things interesting for companies.
As the use of IoT grows (global IoT market is growing at a rate that data scientists do not think will reduce anytime soon), enterprises are beginning to see the importance of artificial intelligence, analytics, and business models that transform operations. However, their data management processes and tools currently at use are not able to keep up with the complexity that comes with modern digital businesses. This is where DataOps comes in. It enables intelligent data operations by getting the right information to the right place and at the right time, thus improving enterprises’ efficiency.
However, with the accelerating adoption of IoT by enterprises, there are a number of problems that they need ...
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