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MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Skill Level: Intermediate | Genre: eLearning | Language: English + srt | Duration: 1h 3m | Size: 119.3 MB
Data science can be generally defined as the process of making data useful, and data engineering is a key part of how and why. If you think of data science like a race car, the data engineers are the pit crew. They're not driving the car, but they make the car much easier to drive. Data engineers make sure the data flow is running smoothly, monitor systems, anticipate problems, and repair the data pipeline whenever problems arise. They extract and gather data from multiple sources and load it into a single, easy-to-query database. In short, data engineers make data scientists' lives easier.
In this course, Harshit Tyagi explains the fundamentals of data engineering. He covers key topics like data wrangling, database schema, and developing ETL pipelines. He also details several data engineering tools like Hive, Hadoop, Spark, and Airflow. By the end of this course, it should be abundantly clear why the data engineer is one of the most valuable people in a data-driven organization.
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