Trends Tool, a tool for abstract textual data analysis used for additive manufacturing trend

This paper contributes to addressing the gap between supply and demand in data science. The proposed solution to high demand and low supply is to make a tool that: separates technical proficiency form domain knowledge in the required skillset of the analyst, enlarging the amount of people that qualify for the job, increasing supply. The tool is also meant to streamline the data science process as a whole, resulting in a faster process, decreasing demand. The tool is designed to address high-level abstraction analysis goals of textual data such as tweets, emails, articles and publications. The tool was designed to analyze trends but can be used for other purposes. The end from using the tool can be described as a very extensive segmentation. A better understanding of the researched concept can be gained. The tool is designed using an example scenario in analyzing Additive Manufacturing as a whole. In conclusion, the tool has some modularly defined functionalities that are understandable and easy to use for someone with domain knowledge. Making it possible for a person without technical proficiency to conduct complex analysis.