Data Science: Developers v analysts

Data Science implies that analysts become more like developers. They need to develop data tools which can be used by themselves as well as less trained people. However, there are some principal differences between analysts and developers. Developers work on very prescriptive problems and leave most testing to the users (think beta). Analysts on the other side need to work on shorter briefs (‘find out what happened here’) and are responsible for the validity and robustness of their analysis (code). Now by adopting a developer attitude, analysts lose some of the rigour and self-reliability which signifies a great analyst. What do you think?

Leave a Reply

Your email address will not be published. Required fields are marked *

You may use these HTML tags and attributes: <a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code class="" title="" data-url=""> <del datetime=""> <em> <i> <q cite=""> <strike> <strong> <pre class="" title="" data-url=""> <span class="" title="" data-url="">