Data engineering can be clearly defined but the job of a data engineer rather not. If you look at the tasks of data engineers in two different companies or organizations, you may hardly see them as the same job description.
We have learned that data engineering and data analytics overlap, especially among mid-sized companies or freelancers. Our academy lessons are designed to prepare you for this diversity.
As a data scientist, you are responsible for ensuring that and how data is collected in a company, government agency, scientific institution, or organization. By the way, this often does not involve personal data.
You structure and model the collection, storage and processing of data and data streams. The data flow of your employer or customer is in your hands. This increasingly includes cloud solutions.
This can be a one-time process as well as monitoring, optimizing and augmenting constant data streams from source to storage and processing to display.
For example, it could be about the constant flowing data of monitoring a production process, a traffic flow, weather stations or whatever. But you could also be part of a team of developers who are constantly creating new variants of engines, materials, chemical substances ... ... Or you could research concrete processes in societies for NGOs, with the goal of finding practical or political ways to change the situation.
There are few limits to the possibilities.
In addition to structuring and storing data, data engineers are often involved in identifying the necessary data and analyzing it. This means that you lay the foundations for insights on which decisions are made (sometimes in real time).
So you'll be expected to understand the processes in your organization, know why data is being collected and what will happen to it. You may be involved in figuring out what data is critical to what issues and where to get it.
You need to be comfortable with math and statistics, programming and programming languages, databases, etc. In addition, you need to be able to represent data so that non-experts understand what it contains and means.
Data Engineering is a complex, diverse field that will challenge you on a daily basis.
We have learned that data engineering and data analytics overlap, especially among mid-sized companies or freelancers. Our academy lessons are designed to prepare you for this diversity.
As a data scientist, you are responsible for ensuring that and how data is collected in a company, government agency, scientific institution, or organization. By the way, this often does not involve personal data.
You structure and model the collection, storage and processing of data and data streams. The data flow of your employer or customer is in your hands. This increasingly includes cloud solutions.
This can be a one-time process as well as monitoring, optimizing and augmenting constant data streams from source to storage and processing to display.
For example, it could be about the constant flowing data of monitoring a production process, a traffic flow, weather stations or whatever. But you could also be part of a team of developers who are constantly creating new variants of engines, materials, chemical substances ... ... Or you could research concrete processes in societies for NGOs, with the goal of finding practical or political ways to change the situation.
There are few limits to the possibilities.
In addition to structuring and storing data, data engineers are often involved in identifying the necessary data and analyzing it. This means that you lay the foundations for insights on which decisions are made (sometimes in real time).
So you'll be expected to understand the processes in your organization, know why data is being collected and what will happen to it. You may be involved in figuring out what data is critical to what issues and where to get it.
You need to be comfortable with math and statistics, programming and programming languages, databases, etc. In addition, you need to be able to represent data so that non-experts understand what it contains and means.
Data Engineering is a complex, diverse field that will challenge you on a daily basis.
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