How can Data Analyst be called the most boring job? (2024)

Sometime ago I received information from one of my colleagues who mentioned that CNBC published an article which stated that Data Analyst is the most boring job. I was surprised for a moment, because throughout my professional work as a Data Analyst, I always face new challenges and different contexts every day. Which is what forced me to continue learning to pursue many different contexts of knowledge, public policy, marketing, social education, technology products and even finance. For this reason, I finally decided to do a deeper search to find a reason that was sufficiently data-based from what was conveyed in the article.

Throughout my professional career, I’ve always had the perception that a job in Data Analytics is quite a difficult job because I have to constantly deal with many diverse and challenging problems. So choosing the right team wasn’t easy until I realized that this job doesn’t always have the same scope or responsibilities in different places.

Be on a particular team

Have you ever seen a job vacancy like “Data Analyst-Payment” or “Data Analyst-Ads & Promotion”? Yes, this means that the scope is only concentrated on certain teams (or so-called eg tribes or squads). Of course, in a case like this, the context of the data analysis carried out becomes more specific with limited knowledge of the data area.

This will be different for data analysts serving multiple teams (shared). The context and area of data knowledge that must be worked on and for which they are responsible has certainly become wider. So it is very normal to need more time in terms of exploration and pursuing the knowledge they need to have.

Technical skills and tools used

Even though they have the same job title, it doesn’t necessarily describe the same skills for each individual. Every company/organization has different maturity levels in data-driven decision making. Of course this will link the technical skills of a data analyst needed and what tools can be provided and become a data team environment. For example, some perform simple analyzes with excel or spreadsheets, but others perform complex analytical methods that require programming languages.

Report: numbers and stories

One of my colleagues once told me that as a data analyst, his previous daily job was to collect data and change numbers in reports (with the same template) periodically. My thought crossed, if “just replacing the numbers” then of course this job becomes tedious.

On the other hand, I also know that there are data analysts who have to deal with different business questions or problem statements every day. They are required to tell further stories using the context of the question owner (stakeholder). From here we can agree on which needs are just numbers, and which needs are answers to questions in the storyline.

From the various points of view that I have presented, of course I agree that being a data analyst can be a tedious job. In my opinion, why can it be boring? Because it might not be challenging enough for us. So what we really need is a ‘challenge room’ that comes from the questions of decision makers (stakeholders) or can also come from our ‘anxiety’ and ‘wild ideas’ as a data analyst. This is what I always believe in and I tell my teammates, “Technical skill is one thing, but how we communicate the story is something.”

So as a data analyst, don’t be boring. Don’t accept requests without asking. Do not just answer or give a number of what is asked. Explore, listen more actively, and broaden your perspective. If we are asked to do analysis to help a commercial team, then think like them, use their language, and seek knowledge of their field. Because without the proper context of the story, what we are given is just a number, nothing more.