What is it like working as a data analyst? What is a data Analyst's role, position in a company, salary and daily life? In the following section, Wild Code School offers you a general overview of what it means to work as a data analyst in the digital sector.
The shortage of data analyst profiles
By meeting our partner companies from 19 campuses that make up its network, Wild Code School has identified data analyst profile as a priority issue on the job market.
The data specialist profession maintains the image of a high level of technicality, reserved for engineering courses and with a strong mathematical component. In fact, analysis tools and algorithm programming languages have developed and facilitate data processing at a large scale. This profession is now diversified and there are recruitment needs at all levels, offering interesting career paths.
Data analyst job
A data analyst's work is based on pure and hard data. It is one of the pillars of a strategy based on data, the famous "data-driven" strategy. Their main function is to analyse the data and extract useful information to help the company grow.
They start by collecting the raw data. They will then carry out data structuring work, this is called the lower layers. Then, they will create ways to graphically visualise the data.
They may work with several departments of the company (marketing, operational management, communication, studies and development, product management, support functions, etc.). Data analysts work within the team, most often with clients (internal or external), project managers and other data analysts.
Average salary of a data analyst
The salary for a sought-after data analyst varies according to your geographical location. You can check the Glassdoor platform to learn how much data analysts earn in your city. For instance, the average salary of a data analyst in Madrid is 30k€ per year, 41k€ in Paris, 44k€ in Berlin and 32k£ in London.
Do you speak data analyst? Terms to know.
Data Preparation (or data preps): all that is data collection and manipulation (it's also a category of tools).
Data Visualization (data viz): this includes dashboards, visualisation, and reporting.
Data Science: a discipline that relies on mathematical, statistical, computer and data visualisation tools.
Big Data: data sets so large that they exceed the analysis capabilities of traditional IT tools.
Artificial Intelligence: this "intelligence" is often a program trained to work with Big Data.