Internet of Things in Data Science

Machine learning is a subset of artificial intelligence. While data science is an interdisciplinary field to extract knowledge or insights from data. Nowadays, improving business productivity and performance mostly depends upon collection and analyzing data. Businesses have been processing data but the introduction of Internet of Things acts like a game changer. Data collected through IoT is analyzed using different techniques as compared to that collected traditionally. Moreover, Data Scientists require more sophisticated skills for analyzing IoT data. 

A business has multiple sources of generating data but IoT changes the data which has some values. In comparison to traditionally collected data, one generated through IoT is in real time and this is immensely useful for industries. Another way to differentiate between traditional and IoT-generated data is traditional data does not change.

For example, if a device is used to select a city from a specific country, the list of the cities is going to remain the same and on the other hand, if data is being rendered from a device, it’s going to have an IP address that delivers the information to other devices with IP addresses. This information may be collected by a server that is accessible to different companies. So let’s say one of these devices is your smartphone and is collecting information on your online shopping habits. So if the server is accessed by an online store, they will have your information.

Now you understand that how IoT is being used to collect data, it is obvious that there is an excessive amount of data being collected at any given time. It also makes the data complex. Moreover, the way IoT-generated data is stored and processed also varies.

As the popularity of IoT increases, flow of data lies in the future. It is bound to the change the way we have viewed Data Science for some time now. The boom in data is not only going to require better infrastructure but also smarter Data Scientists. We will need an infrastructure that can reliably process a constant stream of complex data. And it will be a serious waste of time and money if we can’t use this surge of data to make more and better sense out of it. Therefore, this explosion of data should be an opportunity for data scientists.

By taking advantage of Data Science for IoT, we are not only helping the business industries in terms of better performance and profit. In fact, we can create a better world. With smarter analytics, we can resolve multiple problems faced globally.