This article is useful to read for my fellow computer science mates interested in the data that revolves around us as well as those with strong mathematical backgrounds. This article gives you a solid idea of the expectation of a data analyst as well the possible work load awaiting in this career path.
Being a data analyst means turning raw and for some even incoherent data for some into insightful information. It often means cleaning up datasets, analyzing trends or presenting our findings with the help of a dashboard.
A data analyst is somehow who reads, understands and makes up some sort of story with the data. An analyst will find the reasons behind a spike in sales based on the type of consumer, location and many other factors for example.
They meet with stakeholders, data engineers and other teams to develop and understand where the exploration of the data is heading. A data analyst is a programmer as well, they use mainly Python and SQL to showcase patterns or trends within the datasets. They must present the findings that align with the company's goals and help guide data driven decisions.
If the company produces, stores, or deals with data, an analyst will surely have a place. Nowadays companies are big on data as it can shape the course of expansion, the rate of the expansion and maybe even through data come to an idea of how much it can expand.
There is many ways of becoming analyst, the most common way is through a computer science program at college or university level. The skills needed for the job a highly mathematical based. A bachelor in a mathematics with a computer science concentration can help achieve such a role. Academics is not everything, if motivated you can achieve such a role with bootcamps, certification and some self-taught lessons.
A data analyst can earn 51 000$ and up to 140 000$ with a senior role. That said the average salary is around 70 000$.
A data analyst needs to be comfortable coding in Python, they also must know how to pull a query using SQL. Additional training needed would be anything mathematic, statistique and algorithmic related.
The dangers of being a data analyst is getting fed up with numbers, not being able to find sense in them. With the evolution of AI, it can also be a danger to be replaced by artificial intelligence.
AI will surely and probably does already a good part of the automation, making an analyst job lighter. As humans, we can do more than AI. We can understand the context, we can ask the correct questions, we can communicate with people, we can take into consideration metrics that matters. The role of a data analyst is not close to be replaced.
Like any other job, retiring is a choice. Typically, they will retire at 65 years old.
In my career trajectory, I am in my second year of DEC in computer science. I wish to make the jump to university in a Mathematics concentration in order to really branch out to be a data analyst.