This course is designed to provide you with a foundational understanding of how modern data ecosystems work. From data pipelines to ETL processes, and big data handling using Apache Spark, you’ll explore the essential tools, techniques, and technologies that drive decision-making in today’s data-driven world. Whether you’re an aspiring data engineer or someone interested in the mechanics of data handling, this course will lay the groundwork for your journey into the exciting field of data engineering.
Engineering Data Ecosystems: Pipelines, ETL, Spark
Gain insight into a topic and learn the fundamentals.
Beginner level
Recommended experience
1 hour to complete
Flexible schedule
Learn at your own pace
What you'll learn
Identify and describe the components and importance of data ecosystems.
Understand the basic structure and function of data pipelines.
Recognize the steps involved in ETL workflows and their role in data handling.
Gain an introductory knowledge of big data and the application of Apache Spark.
Skills you'll gain
Details to know
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Recently updated!
October 2024
Assessments
1 assignment
Taught in English
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There is 1 module in this course
This course serves as an introductory course aimed at unraveling the complexities of data ecosystems. It's tailored for individuals at the onset of their data engineering journey, emphasizing the construction, management, and optimization of data pipelines, the essentials of ETL (Extract, Transform, Load) workflows, and an introduction to big data processing with Apache Spark.
What's included
12 videos4 readings1 assignment2 discussion prompts
Instructor
Offered by
Recommended if you're interested in Data Analysis
Whizlabs
Duke University
DeepLearning.AI
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Frequently asked questions
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