The ability to analyze and understand large sets of data quickly and accurately is vital to success in modern factory environments. Critical factors such as big data and augmented analytics play key roles in a factory’s ability to operate efficiently, while avoiding potential errors. Below we’ll walk you through the concepts of big data and augmented analytics, the advantages they provide, and various ways they influence the modern factory environment.
Big data is defined as “extremely large sets of data that may be analyzed computationally to reveal patterns, trends, and associations”. Now, how does this translate to the factory setting? With the dawn of IIoT, smart devices and sensors, and automation, more data and information is available for consumption than ever before. The goal of every factory is to take that raw data and transform it into actionable information. Utilizing that information gives you real-time insights into the day-to-day functions of your business. Moment data allows users to instantly interpret and oversee operations - whether that be benefitting by correcting inefficiencies or avoiding potential machine malfunctions, which may lead to future losses.
Breakdown of various Big Data sources
So now that we have such a great influx of raw data, how do we go about interpreting it in meaningful ways? Turning that data into actionable insights is done with the help of augmented analytics. Defined as “the use of enabling technologies such as machine learning and AI to assist with data preparation, insight generation, and insight explanation to augment how people explore and analyze data”, augmented analytics is used to make that raw data easy to understand for users. Instead of pouring through hundreds of thousands of data entries, augmented analytics helps compile and summarize data into easily digestible snippets. This streamlines several complex, tedious processes for your business, saving both time and money.
Working together, both big data and augmented analytics allow operators to have a clearer picture of what is happening moment-by-moment in their factory. Collecting and analyzing data in real-time allows for more flexibility, not only the ability to predict potential errors but also the opportunity to improve existing processes to function more optimally.
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