The trends Internet of Things (IoT) and Industry 4.0 bring intelligence to components and everyday appliances, resulting in a flood of data that is increasing exponentially. For instance, in today’s production environment, technically advanced machines are already continuously sending data about the current status and sending alerts when maintenance is required.
Big data is a technology that collects and analyzes the kind of data created by those processes. Big data’s greatest strength, however – the quantitative foundation – is also its greatest weakness. It is difficult to derive concrete action guidelines or actionable meaning from an analysis of current solutions, if the point is to make business decisions based on the collected data.
Hence, the current trend is pointed squarely towards ‘humanized big data’: Information should be processed in such a way that non-data scientists can also derive clear answers ̶ ‘actionable insights’ ̶ from big data analyses and use them as a basis for decision making.
This requires an approach that is more qualitative than quantitative, as well as a high degree of visualization of the data.
The idea of humanizing data may seem counterintuitive on its face, but it’s really not. As our experts point out, data starts with humans. Therefore, at some point, humans must also be involved in the processing of data.
Humanizing Big Data argues that data isn’t really something that can be fully automated. Rather than handing the entire processing task over to super-smart machines, the human element, so integral to understanding the results, can’t be removed from the analytics process.
Some of the interesting questions that humanizing big data will solve are: What’s the best approach for the small business that wants to get into data analytics? Are we forgetting the customer while we embrace the soulless technology that delivers the data? And what about the future? Can we extend big data to do more than just improve marketing?
Humanizing Big Data makes it accessible for analysts who operate in today’s enterprise business units, giving them capabilities usually available only to IT. It’s rendering data into information that is easily accessible and highly relevant. It’s making analysis based on Big Data effortless and natural. Instead of relying on specialized skills in programming and statistics, data can be humanized by adding appropriate context and offering straightforward tools for building analytical applications. Humanizing Big Data means working with the data directly so that it tells its story. Having the full story leads to business insight. It also means a new ability for data analysts to hone their craft and expand their ability to do analytics independently. They become, in effect, data artisans.