Required Key Skills to Become a Data Analyst
The data analyst not only needs technical skills to be competent, but also important soft skills. The union of the two types of skills forms the successful professional.
Do you know what it is and what a data analyst does?
Professionals in this area are responsible for collecting, investigating and representing the information that a company stores. Thus, your role is to extract the most relevant data from a business and ask questions that help filter it and turn it into insights.
It is also the role of the analyst to conduct preliminary studies on the data, use data mining techniques and understand the concept of querying (SQL), employing all this knowledge in the discovery of patterns, which need to be represented in graphs, tables and models capable of guiding the decision making.
Interested? So, if you want to understand in depth what it takes to become a data analyst and what are the courses that can help you in this task, keep reading this post.
What skills does a data analyst need to have?
To become a successful data analyst, the professional must have different types of skills, which are known as Soft Skills and Hard Skills. The first type are non-technical skills and are related to each individual’s education, their life experience — they can be good communication, problem-solving skills and critical thinking, etc.
While Hard skills, also known as technical skills, refer to the in-depth knowledge that the professional has about a certain area — in this case, data analysis. Each of these knowledge helps the analyst in a specific way, and in the topics below we will show you why.
Soft Skills
Critical thinking
Critical thinking is essential for the data analyst because it helps him to really understand the problems he has to deal with. Only in this way is he able to judge the best approach to modeling the information at hand and answering management questions. In addition, with critical thinking, the individual puts aside his subjectivity and analyzes problems objectively, seeking to solve problems through grounded reasoning.
Problems solution
A competent data analyst is one who knows how to find suitable solutions to problems that arise while working. The skillful problem solver is not only able to use the best methods to solve complicated situations, but also to identify the reasons that created the problem. Thus, he acts to prevent new adversities from arising in the future.
Good communication
This skill is not just critical in data analysis, but in all professions. A professional who does not communicate well cannot have good relationships with his co-workers, which can cause friction within the company environment. When working with data, the analyst needs to clearly communicate his findings to both technical and lay audiences.
Commercial sensitivity
The analyst should not be concerned only with the technical issue related to the data. He needs to understand the company’s goals and the niche in which it operates. In this way, the professional will have more resources to solve possible problems, so this will help in the growth of the enterprise.
hard skills
Ability to program
Knowing how to program is another point that needs to be worked on by the data analyst. Languages like R and Python are the most used in the field, helping to handle large groups of information with ease — other programming languages that can still help are Java, Scala, Clojure, Octave and C++.
Data architecture
Understanding how a company’s data is structured is critical for the analyst to troubleshoot. After all, once he can understand how a business’s data is stored and made available, he can make changes that make predictive models even better.
Mathematics knowledge
Anyone who works with data needs to have knowledge of statistics. Analysts and scientists of this type of information work with mathematical models and must know how to use them. In addition, this ability allows you to perform in-depth analysis and identify relevant patterns and relationships.
Acquaintance of artificial intelligence (AI) and machine learning
Knowing how to employ artificial intelligence and deep learning tools in data processing can benefit the company. This is because applications help identify information that will be useful for the desired objective or not.
In which courses can I learn data analysis?
There are several courses available for anyone looking to become a data analyst, but choosing the most appropriate one will depend on the industry you want to work in. With that in mind, you can create an efficient study plan and define what you need to learn before entering the market. Currently, some popular fields in data science are biotechnology, finance, marketing and technology, but there are still many others where your knowledge could be useful. Data science can be studied at a distance or in face-to-face courses. In addition, some fundamental courses are data modeling and data visualization.
Where to start courses for data analyst?
A good way to start studying data analysis is to think about the curriculum you want to present in the future. Check out some vacancies in your area of interest and find out exactly what specifications are required by contractors.
Be that as it may, it is worth noting that the more data companies produce, the greater the importance of the analyst in the business context. Today, 2.5 quintillion pieces of data are produced every day — and it’s as miscellaneous as you can imagine.
The data analyst is the only person capable of navigating through them deftly, so the market for their services is expanding daily and fast. So, given what we’ve seen here, consider investing your studies in the area to secure a stable job position as a data analyst for years to come.
