Data engineering – the engineering science of big data

You’ve probably heard data science before, but data engineering?

Data Engineering vs. Data Science

Obviously, a data scientist’s success is only as good as the data they can access. Data exists everywhere – including in companies – and in a wide variety of formats. It is collected in databases or text files.

And this is where data engineering comes into play. This is because a data engineer builds pipelines that convert precisely this data into formats that the data scientist can use. This is why data engineers are just as important as data scientists, but are often less visible. They are the ones who are far removed from the end product of the analysis and prepare big data.

Race cars – build or drive?

A racing car driver always has the privilege of competing and driving against his rivals on the track. He is the winner who is celebrated by and in front of the audience. However, it is the constructor who brings the engines to peak performance. Various exhaust systems are tested and everything is optimised until the rider can drive a powerful, robust machine.

What is Data Engineering?

But what optimises data engineering? A data engineer prepares data for analytical or operational purposes; this includes setting up data pipelines to bring together information from different source systems. They also focus on the integration, consolidation and cleansing of data. He also concentrates on structuring data for use in individual analysis applications.

Data engineers therefore generally deal with structured data on the one hand and unstructured data sets on the other. For this reason, they must be familiar with a wide variety of approaches to data architecture and application. In addition, a variety of big data technologies, such as a constantly growing selection of open source data collection and processing frameworks, are included in the data engineer’s toolbox.

Data engineers as a binding agent

Data Engineers are the link between Big Data and Data Scientists. Thanks to their engineered platforms, they enable data scientists to process all information

Related posts