Analytics

5 traits of a good data analyst

29th Jul `17, 11:00 AM in Analytics

Data analysis is a highly technical profession that requires multiple skills and characteristics to be successful at work….

Finn Pierson
Finn Pierson Contributor
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Data analysis is a highly technical profession that requires multiple skills and characteristics to be successful at work. In this article, we’ll dive into a couple of those characteristics that help data analysts do their job well.

In a study by RMS Results, there are 13 traits which all good data analysts share. We will focus on five of them.

Methodical

A good data analyst must be systematic in his or her approach to problem solving. Data analysis requires someone who can carefully and clearly create a step-by-step guide to instruct others of what they must do to the data they receive. Any ambiguity or misunderstanding on the data analyst’s part could lead to a serious misinterpretation of the data.

Self-Motivation

It’s one thing to follow directions for a project and find results. It’s totally different to be self motivated and complete tasks by yourself. A good data analyst is able to look at the data and tell why it is important to their boss and their company. Their reports should reflect this understanding and cater to the needs of those who will read them. A good data analyst doesn’t need to wait for their boss to clarify what they need to do. A good data analyst is self-motivated and proactive and does what they need to do without waiting to be told.

Imaginative

Imagination isn’t just for kids. To make data truly unique, the perfect data analyst can visualize data in new ways. This is what makes data that has been seen before fresh and innovative. For instance, rather than using a static model for data, the data analyst could utilize D3 or install spark to make a “living” model of the data. A good data analyst can tell a story with the data to help others better understand it and its importance.

Skeptical

No data gathering process is perfect and all data sets will have their flaws. For the data analyst, skepticism is just a recognition of this fact. Data analysts need to be able to recognize flaws in their data and should include those flaws in their reports. They should also be able to clearly explain how these flaws can possibly skew the results of their analysis. A data analyst should cover all views of the data, not just the ones that seem favorable to the study.

Capable of Spotting Patterns

This is an important trait since data relies heavily on patterns. A good data analyst can look at different data sets and identify trends and what triggers those trends so the company can either replicate those results in the future or avoid them depending on the given pattern.

Conclusion

We have looked at some of what makes a data analyst good at their job. A computer can take data and manipulate it, read it, analyze it, and determine its patterns, but a only a good data analyst can make that data meaningful to other people. They can turn numbers into meaningful patterns that others can use.

We also should take into consideration that the data analyst should be on time, qualified, and ready to work in a data driven environment. No amount of analytical skills can make an employee exempt of basic employee courtesy.

Data analysis is incredibly fascinating and informative when used in the right way. Top notch data analysts can help their respective companies discover why business is the way it is by using data that can be often hard to interpret. If you’re looking to improve yourself as an data analyst, these traits will help take you from Ok to amazing.

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