Role of Data Analytics in IoT

Today, new sensor, mobile and wireless technologies are leading to the evolution of Internet of Things (IoT). Importantly, the true business value of the IoT lies in analytics apart from hardware novelties.

Data analytics is examined as a procedure to examine small and big data sets with different properties to extract conclusions from the data sets. These conclusions are in the form of statistics and patterns that help businesses to make effective decisions. It plays a major role in the success of IoT applications along with investments. In fact, analytical tools permit the business units to use their data sets efficiently. Few points have been mentioned below:

Volume

Today, without new analytics tools, it will be difficult for the data scientists to generate understanding from IoT data.

With a rise in explosion of data, analytics will be relevant to businesses. Businesses will have to invest in state-of–the-art analytics software to process and evaluate data.

In fact, to adopt to IoT data volumes, organizations will have to make changes. It is said that in a few years, zettabytes of data will be coming from IoT. That said, to accommodate this volume, there will be a change in tools, processes, and technology.

Structure

The Internet of Things delivers data in various formats, making it difficult for anyone wishing to examine the data. There isn’t an industry leader for the Internet of Things and no specific technology protocols. The old analytical tools that depend on SQL databases will need to be substituted with new tools in order to process datasets being produced.

Driving Revenue:

Data analytics in IoT investments allows businesses to get an insight into customer preferences. This leads to various services and offers, catering to customer demands. Overall, this improves the revenues earned by businesses.

Moreover, there are various kinds of data analytics that can be applied in IoT investments to reap benefits. These are some of them:

Streaming Analytics:

This kind of data analytics is known as event streaming processing and examines big data-sets. Real-time data assets are analyzed to detect urgent situations. IoT applications on the lines of financial transactions, air fleet tracking, and traffic analysis can gain from this method.

Spatial Analytics:

This is used to examine geographic patterns to understand spatial relationships between physical objects. In fact, location built IoT applications like smart parking applications can gain from this kind of data analytics.

Time Series Analytics:

This type of data analytics is built upon time-based data which is examined to expose trends. IoT applications, such as weather prediction and health monitoring systems can gain a lot.

Prescriptive Analysis:

It is a combination of predictive analytics and descriptive. It is used to comprehend the ideal steps to be taken in a certain manner. Interestingly, commercial IoT applications can use this type of data analytics to make worthy conclusions.

At the same time, with profound changes in the advancement of technology, there are certain areas in which data analytics can be used in IoT. For example, actionable marketing can be done by using data analytics in the product usage.

Moreover, IoT analytics will allow safety and surveillance through video sensors.

That’s not it.

Healthcare is an important sector in all countries and the usage of data analytics in IoT based healthcare applications can offer immense benefits. For example, there can be reduction in healthcare costs, augmentation of telehealth monitoring, and increased diagnosis with data analytics.