By increasing the number of sensors and monitoring processes more closely our customers can generate increasing amounts of data. This data is then used to analyze and understand the processes and ultimately deliver a better product and more efficient production.
The growing volume of data opens up many possibilities, but also presents challenges. When you are looking for useful relationships and information in large amounts of data you first have to solve the problem of managing and analyzing the data. Many customers tackle this by enlisting expensive experts in machine learning and coding to work closely with domain experts.
Since its launch, our Sympathy for Data tool has offered users the ability to extract and process large amounts of data from many different sources and in various formats. By incorporating machine learning directly in this tool, domain experts are able to use statistics and machine learning directly. This allows them to analyze data without the need for coding.
Instead of requiring a mix of machine learning coders and industrial users, as before, we can give non-coders the basic skills in statistics and an overview of machine learning practice.