Its interesting that these two job titles and their scope are often either conflated together or there are some for their own personal agenda says that (1) Data Analyst should be paid less than Data Scientist or (2) Data Analyst are just playing a supporting role to Data Scientist. I want to state here, I do not believe these two points.
I will be sharing from one perspective and discuss why I do not believe in the above two points and argue they should be seen as equal. This issue is inspired from a discussion with Eric Sandosham, my co-instructor in Visual Analytics class conducted in Singapore. He is an established, experienced and passionate advocate for Data Analytics and we always have very thought-provoking discussion on the data industry.
Data+Brain Power+Computation Power = Actionable Insights
From the above formula, we can see that be it data analyst or data scientist, there are certain amount of need for both brain power or computation power. From the type of analysis, Data analyst FOCUS a lot more descriptive and diagnostic analysis. Data scientist on the other hand deals more with predictive and prescriptive analysis. In terms of tools and data analyst use MOSTLY visuals, summary statistics and the lesser computationally intensive tools. Compared it to the data scientist, they deals mostly with more sophisticated algorithms that will take much longer for a human to compute with calculator, or in other words, more computationally intensive.
Now for a Data Analyst, to produce quality analysis, relatively speaking it requires a lot more brain work because it has to draw what is seen on the MANY visuals and statistics back to the domain it is analysing on. There is a lot more “connections” it needs to make and create a coherent “story” that is to be shared later on in a business meeting. The brain power required is a lot more as compared to the Data Scientist looking at a single machine learning or optimization algorithm and providing the insights.
With the last two paragraph that we have seen, we can can see the following:
Computation Power: Data Scientist » Data Analyst
Brain Power: Data Scientist « Data Analyst
A few points I want to make before I conclude. (1) I am not trivialising both Data Analyst and Data Scientist. I do think the work they do are important if a company wants to be data-driven in their decision making.
What I want to dispute here is that the two roles, Data Analyst and Data Scientist are very different and thus the value they bring to the company is different as well even if the raw materials used by the two roles are data. I hope that after this issue, you have a better idea what they do and dispel the two myths I mentioned at the start of this issue and that is
(1) Data Analyst should be paid less than Data Scientist
(2) Data Analyst are just playing a supporting role to Data Scientist
What are your thoughts on this? Will love to hear them!
Consider supporting my work! Please share this issue out to demystify! Or you can make a “book” donation and drop me some wisdom! Thank you! :)
Do check out Eric Sandosham’s Medium as well! I’ve learned a lot reading through it. Definitely worth the time spent! Here is the link!
Thank you for the shout out! I have enjoyed our many conversations on this topic.
I like the perspective you are bringing to this argument: that of brain power. For a typical data scientist, their competency lies in computational thinking and computational modelling. For a data analyst, the competency is in data sensemaking and data storytelling. The former is arguably more complicated while the latter is more complex. While both complication and complexity requires brain power, complication can be 'outsourced' to computers, but not complexity (at present). Hence the point that descriptive and diagnostic analysis would require more brain power in general. Diagnostic analysis, in particular, requires a special kind of 'wisdom' to see the patterns and connect the dots ... to see the trail of information signals.
I should be paid more, regardless of my title