Big Data is defined as exceptionally large data sets, potentially numbering into billions of rows and parameters. In manufacturing, big data can include data collected at every stage of production, including data from machines, devices, and operators. The sheer volume and complexity of large data sets and the number of specific tools, techniques, and best practices for working with them have led to the maturation of the field of data science and big data analytics in and around manufacturing.

As data refers to the stored information and recorded operations which were performed by the computer in various forms, big data can be understood as the same data being present in huge amounts and numbers. This consists of information provided and both humans and the devices and on almost everything.

Big data analytics helps to analyze risk patterns, maintain workflows, improve the quality of the processes, production, and others. Big data solutions analyze, collect, and monitor a large volume of unstructured and structured data generated from a variety of sources such as production unit, product quality, factory floor, etc. Big data technology helps to uncover newer trends and patterns and provides actionable insights to businesses.

Furthermore, big data is becoming one of the important elements in the manufacturing industry, as it is playing a major role in the fourth generation of enterprise resource planning (ERP) systems. ERP technology is supporting to transform outdated manufacturing facilities into highly automated and efficient powerhouses. The big data technology is set to create a new era for manufacturing as it possesses the ability to engage the process, data, and people. Rising technological advancements is expected to augur well for the big data in manufacturing industry.