Data analyst: the peculiarities of the job

What skills does a data analyst need?
Programming skills. Programming languages are used to automate work. They are used to write database queries, process data and generate reports. Most commonly, a data analyst is expected to be proficient in Python, R and SQL.

Knowledge of maths and statistics. A data analyst needs knowledge of probability theory, linear algebra, mathematical analysis and advanced statistics. This is important for analysing data, such as finding patterns and anomalies, and making predictions. Many of the mathematical functions are already implemented in Python and Excel functions, so understanding the theory is important.

Understanding the needs of business clients. An analyst should have a good understanding of the business they are working with. This is the only way he or she will be able to determine what his or her findings mean for the business.
In the blog of Magenta Favorita Unipessoal we continue our series of publications about different specialities in the field of Information Technology. Today we are going to talk about a profession at the intersection of IT, management and mathematics. A big data analyst or data analyst is a specialist who analyses, interprets and identifies patterns in data sets. Businesses use the results of the analysis to make management decisions, create new offerings for customers and launch new services.

If we use images to describe the nature of the analyst's work, we can distinguish three roles that the analyst plays in the business:
  • Scout. An analyst has to find out what is going on in a particular area, company, market, etc. To do this, they use databases, sales reports, survey results, website analysis, etc.
  • Diagnostician. Once the research has been carried out, it is necessary to analyse all the indicators obtained, draw conclusions and make recommendations. Specialists use regression analysis, clustering and machine learning algorithms to build models depending on the business problem.
  • Interpretation. The analyst must be able to explain in plain language to all stakeholders what is happening and what steps need to be taken. Results are often presented in the form of charts, graphs, tables using Excel, SQL, Tableau, Power BI, Python programming language.
Be able to communicate with non-technical people. An analyst interacts with business people much more than, say, developers and data engineers. Therefore, he or she should be able to explain even the most complex things in understandable language, avoiding technical terms. You also need to have a clear understanding of the tasks you are given. If they are vague, you should ask questions until you understand exactly what they want you to do.
Will robots replace analysts?
It is possible to become a data analyst without special training. It is good if your education is relevant to the job: programming, maths, economics, finance. But if your education is in a completely different field - no problem. For example, people who studied history or worked as designers throughout their careers become analysts. If you know how to use SQL and come up with business hypotheses, you can become a good data analyst.

This is a job that will be around for a long time to come. Big data is a key resource for business: it is used in IT, retail, finance, healthcare, gaming, cyber sports, telecoms and marketing. Strategic decisions are made on the basis of analysis and recommendations. Analysts are paid by the head, not the hands. They are therefore unlikely to be replaced by robots. However, analysts themselves can modernise their work through automation. Automate everything that can be physically automated. That way you can maximise the time you spend thinking, hypothesising, testing hypotheses, finding patterns, making recommendations, etc.
Other company articles
Show more