Data Engineering

Data engineering process

First Step

Define requirements

Within this phase, we collaboratively outline key aspects, addressing inquiries pertaining to data origins, potential need for supplementary tracking, designated storage locations, strategies for data preparation, and the consideration of automated processes to ensure fluidity and efficiency.

First Step

Second Step

Retrieve data

The data is embedded in a desired framework, which is brought into agreement with the tool for subsequent storage. With the help of ETL tools, retrieval is also automated in order to keep reports permanently up to date

Second Step

Third Step

Save data

In order to use the data for processing after retrieval, the storage of the data must be optimized. The choice here is generally between a cloud-based system or local data storage.

Third Step

Fourth Step

Process data

In this step, the relevant data volumes are prepared for subsequent presentation. In most cases, only a small amount of precisely processed data is needed to ensure a fast and meaningful analysis. The processing basis depends heavily on the previously selected tools.

Fourth Step

Final Step

Visualize data

There is a wide range of visualization tools from which results can be derived. All of them have specific strengths and weaknesses. Here too, our many years of experience and expertise in the field of data engineering enable us to provide high-quality advice.

Final Step

Optimize with our data engineering offer

Unlock the power of data with precision-driven data engineering solution