Data engineering is a critical discipline that involves creating and maintaining data infrastructure for businesses, enabling data scientists to analyze information effectively. Data engineers focus on the ETL process (extract, transform, load), whereas data scientists analyze data to uncover insights for decision-making. Both roles are essential in harnessing data for strategic outcomes.

1. Data Engineering Preparation | Data
Engineering is a Demanding Field From
Small to Large Businesses.
Introduction of Data Engineering
Data Engineering is a Computer Science discipline that includes storing, processing, and
building raw Data infrastructure for use in other levels. According to the name, it is the
engineering of Data.
The one who performs all the operations of data engineering is known as a Data Engineer.
Its main purpose is to develop a data architecture like a database so that data scientists can
use it to analyze and draw hidden data patterns
Difference Between Data Engineer and Data
Scientist
Both data scientists and data engineers work together to complete their operation of
making data-driven decisions.
Data Engineer
 They focus on developing and maintaining data infrastructure for analysis.
 Data Engineers focus on ETL i.e Extract,Transform,and Load of data.

2. Data Scientist
 Provide insight of the data, that helps in data driven decision making.
 Data Scientists focus on analyzing the data and finding hidden patterns in the data.
Read more : Data Engineer VS Data Scientist
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