As the Internet of Things (IoT) grows, we can now connect practically anything to the web. These devices generate a massive amount of data that needs to be analyzed. That’s where IoT analytics comes in. This post will explain what IoT analytics is and why it’s crucial.

What is IoT Analytics

IoT analytics uses machine learning to automate and simplify many data analytics tasks, which are usually performed manually by data scientists.

It has been estimated that there will be more than 50 billion connected devices by 2020, and this number is expected to grow by a factor of 10 every year. This means that these devices will generate a huge amount of data. The data produced by IoT devices is usually unstructured and highly heterogeneous in nature.

As a result, it isn’t easy to extract meaningful information from the data produced by IoT devices. Data analytics plays a vital role in extracting such information from the data generated by IoT devices.

In this blog, we will see how IoT data analytics can help us extract meaningful information from the data generated by IoT devices. 

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Why should we use IoT Analytics?

IoT is a technology that has been around for a long time but only recently has become widespread. The IoT sector is multiplying and is expected to grow even more in the coming years. We are already seeing the benefits of this technology, as manufacturers have started using it to track their products and make them easier to use. It’s not just a case of buying a new device to start collecting data.

In recent years the term IoT has been used more and more often. IoT Analytics, however, is a new discipline. It helps you to understand the data of all your IoT systems optimally.

IoT analytics enables you to make better decisions, accelerate time-to-market, and improve operational effectiveness by capturing and analyzing data from multiple devices and systems.

With IoT Analytics, you can gain insights into your entire IoT infrastructure and optimize it to get the most out of it. 

[Source: IDC]

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