The data science market keeps growing and becoming more competitive every day. So, one way of standing out is to specialize in specific areas, and having data engineering in the curriculum can be a good idea. Understanding processes, analyses and data processing are just some examples of activities of the data engineer that you learn in a good MBA!
In the digital age, everything we do generates information. So, knowing how to interpret this data and use it is fundamental. And a post-graduation is an important step for those who seek evolution.
Jeronymo Marcondes is the interviewed today here in Blog Next and in this article, the professor of the MBA USP/Esalq in Data Science and Analytics shows the importance of a post-graduation and its relationship with data engineering. Enjoy the content!
The importance of studying data engineering
As we have seen, data engineering is very present in Data Science projects. To Marcondes, there are some main reasons that make a specialization in the area so important and turn data engineering a highlight in your resume. Let’s check out some of them!
Data engineering is essential
The relationship between data science and data engineering is part of the daily relationship of those who work in the area, and their roles compose and aggregate to the processes as a whole.
The professor explains: “Knowledge of the way in which data is worked and collected is essential for understanding the origin of data by data scientists.”
So, the specialization in Data Science is a way of keeping up to date in a market that demands more and more from the professional.
According to Marcondes, data engineering creates the processes that generate databases, from the ETLs (extract, transform, load), and which are the source of study of data scientists.
“The maintenance of these processes, optimization of data response and system feeding architecture are some examples of other attributes of the data engineer”, he explains.
The professor continues: “Briefly, the data engineer ensures that the data that will be used by data scientists is updated, available and with an efficient architecture, which facilitates their consultation.”
Standing out as a data engineer
Marcondes ends with some characteristics that are part of the profile of the data engineer. They are:
- Analytical thinking.
- Deep knowledge of databases, methods of storage and data transfer.
- Will to solve problems.
According to the professor, “the latter is the main characteristic.”
Bonus: the right moment to evolve is now
If you still have doubts whether or not to specialize in the area, know that the market doesn’t wait. An specialization such as the MBA USP/Esalq in Data Science and Analytics is the right choice for those who want to evolve professionally, become relevant and compete among the best.
Did you like to know more about the advantages of having data engineering in your resume? Take this opportunity to start the year with a post-graduation and take this very important step in your career.