Data Scientist vs Data Engineer | Difference Between Data Engineer and Data Scientist
Data Scientist vs Data Engineer | Difference Between Data Engineer and Data Scientist
Become a Data Scientist: https://acadgild.com/big-data/data-sc...
Become a Data Engineer: https://acadgild.com/big-data/big-dat...
Hello and welcome to Acadgild’s YouTube Channel. This is an informative video describing the difference between a Data Scientist and a Data Engineer (Data Scientist vs Data Engineer).
What is the difference between a data scientist and a data engineer?
A data scientist is someone, who is generally good at mathematics and statistics. His proficiency in these subjects makes him a natural analyst. He knows programming and has a penchant for machine learning and artificial intelligence modelling. He has a thorough understanding of the domain he is operating in and uses it to gather business intelligence that can help his organization achieve success. Lastly, he is good at visually and verbally communicating insights from data with a variety of people, including team leaders and business stakeholders. The data engineer, on the other hand, is most likely a programmer from the past. He is proficient at Python, Java or Scala and adept at handling distributed systems for the analysis of voluminous big data. His primary responsibility is creating free-flowing data pipelines using various big data technologies for real-time or static data analytics. The two roles make use of similar skill sets. Safe to say, both - data scientists and data engineers work with big data. They both know programming and understand data analytics.
Nonetheless, the data scientist is a better analyst than programmer, while the data engineer is a better programmer than analyst. The two roles are complementary, not interchangeable. They work best together when they are made to perform tasks that match their strengths instead of the others. With the rise of machine learning and artificial intelligence, a new job role has emerged.
The role of a machine learning engineer lies at the intersection between the roles of the data scientist and the data engineer. The machine learning engineer is most likely a data scientist or a data engineer, who has improved upon their weaker skills.
He is a data scientist with better programming skills or a data engineer with better analytical skills. Having said that, he is still better at one of these skills than the other.
The machine learning engineer is responsible for optimizing programs and systems for machine learning. He is the one of the latest additions to the long list of data professionals. To know more about other careers and trends in data science, subscribe to Acadgild.
To become a data scientist or data engineer, join one of our courses. Thank you for watching and happy learning.
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