Data engineers build and maintain the systems that allow data scientists to access and interpret data. The role generally involves creating data models, building data pipelines, and overseeing ETL (extract, transform, load). Data scientists build and train predictive models using data after it’s been cleaned. They then communicate their analysis to managers and executives.
Data engineering, in a nutshell, means maintaining the infrastructure that allows data scientists to analyze data and build models. Though the title “data engineer” is relatively new, this role also has deep conceptual roots.
Here we are going to understand all this in-depth.
In this session you will learn:
Data Industry and Ecosystem
What Is a Data Engineer?
Data Engineer Vs Data Scientist
Growing Demand of Data Engineers
How Do You Become a Data Engineer?
About: Gururajan Govindan
Gururajan Govindan is a Data Science professional and an Intrapreneur with over 7+ of experience working across domains such as Automobile, Insurance, and Finance. He is known for his expertise in data-driven decision-making. He is currently working on building Data Pipelines and Machine Learning models in the field of Marketing Analytics.
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