As data analytics started getting more relevant to the everyday operations of any organisation, the vacancies for skilled data analysts also soared sky high. Today, practically all the organisations dealing with big data are on a lookout for a upskilled data analysts almost all the time. However, as the need grew, so did the myths associated with it.

Like, for instance, people confuse data analytics with mathematics – a big LOL to them. Little do they know, heh!

Most of these myths spring up because people aren’t aware of the different domains involved in Data Science and often end up confusing one for the other. So, before we get to busting the prevalent myths, let’s first talk a bit about Data Analysts and see how are they different from Data Scientists.

The role of Data Analyst is similar to that of a Data Scientist for the most part. The only difference being that a Data Scientist comes into the picture when an organisation’s data volume and velocity exceeds a certain level that requires more robust skills for sorting through a rolling sea of unstructured data (big data) to identify questions and extract critical information.

Hence, the day-to-day tasks of a Data Analysts slightly resemble that of a data scientist – just at a comparatively smaller scale. Let’s look at the significant responsibilities that surround a data analyst:

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