All posts tagged
data science

Data-driven design: Gathering data for your design project

Getting quantitative insights into your design decisions.

“​This is not the millionth article that will tell you to base your UX decisions on an obscure combination of metrics. Data-driven can be taken quite literally: using real data in the design process from start to finish. This is an overview of where we are now and what lies ahead.”

Peter Vermaercke a.k.a. /petervermaercke | @pvermaer

A Design Thinking Mindset for Data Science

Thinking from a human perspective for data scientists.

“Data science has received recent attention in the technical research and business strategy since; however, there is an opportunity for increased research and improvements on the data science research process itself. Through the research methods described in this paper, we believe there is potential for the application of design thinking to the data science process in an effort to formalize and improve the research project process. Thus, this paper will focus on three core areas of such theory. The first is a background of the data science research process and an identification of the common pitfalls data scientists face. The second is an explanation of how design thinking principles can be applied to data science. The third is a proposed new process for data science research projects based on the aforementioned findings. The paper will conclude with an analysis of implications for both data science individuals and teams and suggestions for future research to validate the proposed framework.”

Rachel Woods ~ Towards Data Science

Simultaneous triangulation: Mixing user research & data science methods

Using DataSci (quant) to get meaning out of UsrRes (qual).

“Simultaneous triangulation is an incredibly powerful tool to generate comprehensive and verified findings. If you only use one method, you could end up with blindspots. If you employ methods sequentially rather than simultaneously, you could run into unexplainable contradictions, like we did at first. The solution is simultaneous triangulation. Next time you have a complex research question, consider using the three-step process to mitigate blindspots and turn discrepancies in learning opportunities.”

Colette Kolenda and Kristie Savage ~ Spotify Design