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What is Data Engineering ?
Data engineering is a process of transforming and preparing data for analysis. It is a branch of data science that deals with the construction, manipulation and maintenance of data architectures. A data engineer is responsible for the implementation of these architectures.
The goal of data engineering is to make data accessible and useful for data scientists so that they can generate insights that can be used to make business decisions.
Currently, one of the most in-demand and fastest-growing jobs is Azure data engineering.
Data Engineering vs Data Science
Data science and engineering are often confused with each other because they both deal with data. However, they are two different fields that require different skill sets.
- Data science is mainly concerned with the analysis of data. Data scientists use statistical techniques and machine learning algorithms to extract insights from data.
- Data engineering, on the other hand, is concerned with the construction of data architectures. Data engineers build and maintain the systems that data scientists use to analyze data.
Data engineering is a prerequisite for data science. Data scientists cannot do their job without the help of data engineers.
