Taxonomy of Big Data and Analytics Solutions for Internet of Things

Abstract

Internet of Things (IoT) works on the principle of data transmission from the sensors to the cloud, where the user receives the IoT data from the cloud by giving valid credentials; here the data are collected by the sensor every day, and the cloud computing data are converted into big data. Big data is the process of organizing and providing the data to the user in an organized way. Data can be stored in any form; it can be either structured or unstructured and sometimes semi-structured. The data generated every day in the globe is around 2.5 quintillion bytes, surprisingly. In the last two years, a large amount of data has been generated. It is extremely difficult for the traditional database to store these different types of data, and retrieval of data will be delayed in case of server congestion, server deadlock, and many similar situations. Thus, it is necessary to replace the traditional database by a big data system. The characteristics of big data include variety, velocity, and volume. The benefits associated with the big data are that the analytics helps the business to grow in terms of revenue by predicting the sales and, as information is wealth, big data is applied in analytics called predictive analysis, where decisions can be taken by the organization based upon the data related to the particular product. Similarly there are other analytics such as prescriptive, diagnostic, descriptive, outcome, and cyberanalytics that are used in different applications such as credit risk finding, patient monitoring in healthcare, students’ knowledge enhancement in academics, and fraud detection in banking. Machine learning, artificial intelligence, and information technology are powered by big data analytics The major big data enabling technologies include Hadoop, Apache Spark, Apache Storm, Cassandra, RapidMiner, R Programming Tool, and MongoDB, and there are many tools used to analyze and provide the data to the IoT user. These tools and analytics methods provide solutions for IoT devices in handling large volume of data.