How Big Data Analytics Can Help Your Manufacturing Business?

Various sensors generate unstructured data, such as vision sensors provide valuable insights. Combined with Big Data Analytics, this unstructured data can help companies improve their operations, management, finance, and supply chain. For example, 52% of manufacturers use visual sensor data to track products in real-time. The benefits of Big Data Analytics Services are numerous for both the manufacturing industry and the wider business community. These technologies will allow companies to unlock unprecedented economic value from their data.

Text Analytics

We generate colossal amounts of unstructured data every single minute. For example, people post 456,000 tweets per minute, make 510,000 comments on Facebook daily, and send 156 million emails daily. Text analytics helps businesses automatically extract meaning from this data. By combining structured and unstructured data, analysts can use text analytics to detect trends and patterns, improve customer satisfaction, detect product problems, and monitor brand reputation.

Machine Learning

Big data is a growing resource, and the amount generated is increasing at an unprecedented rate. According to market research firm IDC, by 2025, there will be a whopping 180 zettabytes of data, more than double the amount generated in 2020. Enterprises need ways to store and analyze this data to keep up with this burgeoning demand. Machine learning can help. 

Predictive Analytics

Predictive analytics for big data are algorithms that predict outcomes based on the analyzed data. The models vary in their mathematical and methodological aspects, but they all have the same goal: to predict future results. There are seven steps in the process, starting from identifying the business objective and then translating that objective into analysis goals. 

Natural Language Processing

You’re not alone if you’ve been wondering whether natural language processing can help your business. It has already proven to be a powerful tool in many interactive applications. These technologies include smartphone assistants like Apple’s Siri, online banking, retail self-service tools, and automatic translation programs. In addition, with the rise of big data, natural language processing can help extract information from these data sources. Such as articles, videos, and forums. By automating and analyzing the information companies collect, they can provide better customer service and decrease the number of calls that traditional live help staff must handle.

Statistics

Despite the enormous amount of big data available, the data is largely unusable unless analyzed. According to IDC’s Digital Universe Study, only 0.5% of data is currently analyzed, while only 3% is tagged. This indicates that not all data has value and could be exploited. This makes big data analytics critical to the future of business. 

Big data analytics describes the most common way of finding patterns, examples, and relationships in a lot of crude information. This information can assist with settling on informed choices light the information. Changing a lot of unstructured crude information from different sources into data items gainful to an association shapes the premise of enormous information investigation. Huge information investigation utilizes progressed examination on tremendous and different enormous informational collections. And they include organized, semi-organized, and unstructured information of different sources and sizes, from terabytes to zettabytes.

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