With the rise of new technologies, companies must manage more and more data. But collecting and managing this data is not enough for companies to use it as a lever for their development, they must also analyze it. Data Analysis has become essential in the Tech field! Do you want to become a Data Analyst by retraining, or simply to improve your skills in the data sector? We tell you more about the job of Data Analyst, the salary, the job and the training of Data Analyst offered by Jedha.
What is a Data Analyst?
Job description Data Analyst
As the name suggests, the purpose of the Data Analyst is to analyze a company's data to make informed decisions on a defined project .
Imagine, for example, that you want to understand the major trends in the purchasing behavior of a company's customers. To do this, the Data Analyst extracts the available data from a database, then analyzes it with various tools to understand the trends that emerge, and thus make decisions on the course of action to follow in developing an adapted product.
As you can see, Data Analyst is a job that is becoming crucial in a world where products are more and more personalized and must correspond as closely as possible to the needs of end customers in order to differentiate themselves and gain market share.
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What are the missions of the Data Analyst?
We find the Data Analyst in everything that has to do with the extraction, analysis and presentation of data. More specifically, he/she may have these tasks:
- Extract data from a database with SQL queries;
- Participate in the improvement of database models;
- Analyze data in Python or R ;
- Perform A/B tests on web data to optimize the design of a site or an application;
- Create dashboards with tools like Tableau ;
- Optimizing processes with Machine Learning;
- Participate in the implementation of Data best practices within the company.
In this context, the Data Analyst must have an in-depth understanding of the company's global environment, its strategies, its products, its market, its competitors etc. And for good reason, the mission of the Data Analyst is to give value to the available data. Find here thefull interview with CandiceStrategy Data Analyst @ Blablacar.
What does a Data Analyst do during a Data project?
If we were to summarise the stages of a data project, we could illustrate them in the form of a pipeline. The pipeline is as follows:
- Data collection: You will need to find the data you need for your analyses. It may be in databases, you will have to scrape it from the web or you can get it from your CRM!
- Exploration: Once you have the data, you will have to clean and prepare it. To do this, we often carry out an exploratory phase called EDA for Exploratory Data Analysis. The objective is to detect outliers or missing values, for example.
- Exploitation: Now that everything is ready, you will be able to use the data for the objective that has been set. For example, in Data Science, you will develop a Machine Learning algorithm.
- Production: Once you have successfully developed your AI algorithm or solution, you will need to put it into production at enterprise level. This involves different technologies and is a separate step.
As a data analyst, you will often work on the exploration part. Although you will have to collect data too, the bulk of your work will be to understand it and make sense of it. You will therefore spend a lot of time performing analyses, exploring data and presenting your results.
What skills and qualities are required?
To become a Data Analyst, you will need to master both technical skills and communication and outreach skills. It is a rather generalist job but we can polarize the skills in a few points:
- Python programming: This is the flagship language in Data today and one that you will need to know to advance. It is what you will use all the time in your work since it is the foundation on which the technologies around data analysis are based. You will mainly need to know libraries like Pandas or Numpy to easily manipulate data.
- Analytics & Statistics: There is a mathematical dimension to Data. Although you don't have to be a trained statistician, it is important that you have a solid grounding in statistics (averages, medians, confidence intervals), linear algebra (managing matrices) and functions (derivatives etc.)
- SQL database management: When collecting data, you will need to use SQL. This is a skill that is in high demand among both data analysts and data scientists.
- Data Visualisation: When you have to present analysis results, you will have to design graphs for example to illustrate your explanations. Very often you will use either Python, through libraries such as Matplotlib, Plotly or Seaborn, or Business Intelligence tools such as Tableau or PowerBI.
- Big Data: Depending on the company's infrastructure, you may have to query Big Data databases. As a result, you will need to know Spark. This is a rarer skill in Data Analysis, however.
- More rarely, Machine Learning: As a more advanced Data Analyst, you might be required to analyze the results of Machine Learning models created by the Data Scientists or Machine Learning Engineers of your company. This would require you to have a solid foundation in Machine Learning to work on and provide strategic insights to the Data Scientists and Machine Learning Engineers.
Communication is the key!
Communication soft skills are essential for the Data Analyst. They must be able to understand and explain analyses to a neophyte audience. In addition to these hard skills, you must also be :
- Good communicator: To be able to popularise certain complex concepts
- Organised and rigorous: If you want to conduct strict, thorough and reality-based analyses
What is the average salary?
Depending on the type of company and the sector, salaries vary, but here is an average salary scale:
Which training courses should I take to become a Data Analyst?
The demand for Data Analysts has been skyrocketing in recent years. Recruiters are open to profiles with very different backgrounds. There is a wide choice of training courses, with various criteria. Here are some ideas for you:
- Online training: Online training offers you the possibility to learn at your own pace, whether you are retraining or simply decide to learn at a distance. Jedha allows its students unlimited access to its JULIE platform, so that you can follow or review your courses. This access to the platform is not only unlimited during your training, but it is also available to you for life.
- Masters in Data: where you can get a more comprehensive education and a state-recognised degree. However, you will need to invest between €10,000 and €20,000 and at least one year of your time.
- Intensive Bootcamp training: It is the right compromise between the flexibility of an online course and the theoretical depth of a master. Data bootcamps have become a real alternative to traditional training because they are very practical and will teach you skills directly applicable in companies. If you are looking for an accelerated training, the bootcamp is made for you. Don't hesitate to look at our intensive Data Analysis courses ranked as the best Data bootcamp training in France!
Depending on your background, your initial level and your aspirations, you will opt for one type of training rather than another. We have written a whole article to help you choosethe best Data training for you. Don't hesitate to have a look at it.
What career progression can you achieve as a Data Analyst?
When you start your career in Data, you will find that there are many opportunities available to you. Once you gain experience as a Data Analyst, you can aspire to positions with higher responsibilities, of which the following is an overview:
- Lead Data Analyst
- Chief Data Officer
You will also be able to make a more horizontal progression with jobs such as Data Scientist to have a broader management of the Data pipeline to manage larger projects in Machine Learning for example.
Our 3 tips for becoming a Data Analyst
If you are interested in getting started in data and are interested in becoming a data analyst, here are some tips that may help you:
- Highlightyour technical and business skills: The knowledge you have of the industry in which you work will enable you to better select and analyse your data. If you don't have any, don't worry! Showing that you are open to all sectors and that you want to discover more is more than appreciated by recruiters.
- Do projects: if you don't have professional experience, that's okay! You can get some by doing open source projects on Kaggle for example. Don't hesitate to do as many as you can to put them in your portfolio.
- Highlightyour background: If you have experience in other fields, it is important to highlight this. For example, you may have experience in marketing or finance and want to change careers. All your past experience is valuable and it will give you a "business" advantage over other candidates who only have technical skills.
Frequently asked questions about Data Analysis
How to become a Data Analyst without a degree?
It is important that you acquire a solid foundation and skill set in data analysis through online training, but also by completing real-world projects that you can present in a professional portfolio to potential employers. You should also develop skills in programming, as well as in the use of analytical tools such as SQL, Python, and Tableau.
What are the 3 main languages to know to become a Data Analyst?
The main languages to learn to become a Data Analyst are : Python, SQL or R.
How to become a Data Analyst?
To become a Data Analyst, you must first learn about each of the criteria we have just listed in this article: missions, skills and qualities required, etc. If you are ready to start a Data training, compare each bootcamp and master available, in order to verify that you are heading towards what corresponds to you.
