A Whole Different League Data Analyst


1. Understand the benefit of a proper analytical method

Most data analysts are aware that the mean is not a good representation of data, yet only a few acknowledge why. Maybe you have heard a data analyst suggested using median, but what are the trade-offs? Why is it better to present the distribution instead?

Data analyst is not about line or bar charts only, we have many fancier type of charts!
sometimes going for 100% right is just not worth the effort.

2. Have a business-oriented goal

Goal determines what we need to do and why we do things. It is obvious that a team would not work if each of the members has a different goal, even though they seem similar. That is why the performance of a data analyst should be measured in regards to the business goal, period. Of course, we can have a data specific goal such as availability of monitoring dashboard or reports. The point is to clarify why the report helps in reaching the business goal and whether the report is the most impactful. What is the point of creating 20 diagrams which do not contribute in taking a decision?

if we care to look, we can see the many things we can do.

3. Be proactive and over deliver

This step is probably the most practical: deliver more than what is requested. You may have heard that “under-promise and over deliver” is a bad advice. However, over-delivering is indeed a useful practice to some extent. In particular, this approach helps to push the quality of questions that we could answer.

over deliver does not mean overwork, and vice versa!
  • what is the underlying problem the business user trying to solve?
  • does this analysis tell the whole story?
  • what is missing?



Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store