After doing these courses, I feel confident creating professional visualizations and dashboards
Shoebur RahmanProcurement Specialist, Giz Bangladesh
Course Description
Understand the Basics of Data Engineering
In this course, you’ll learn about a data engineer’s core responsibilities, how they differ from data scientists, and facilitate the flow of data through an organization. Through hands-on exercises you’ll follow Spotflix, a fictional music streaming company, to understand how their data engineers collect, clean, and catalog their data.
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By the end of the course, you’ll understand what your company's data engineers do, be ready to have a conversation with a data engineer, and have a solid foundation to start your own data engineer journey.
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Start Course for FreeWhat you'll learn
- Define data engineering and recognize its role in building data pipelines for analytics and machine learning.
- Identify key components of a data workflow, including ingestion, storage, transformation, and serving.
- Distinguish between batch and streaming data processing approaches and assess when each is appropriate.
- Recognize the responsibilities of data engineering roles compared to data science and analytics roles.
- Evaluate common data engineering tools and technologies used in modern data ecosystems.
Prerequisites
There are no prerequisites for this course
Curriculum
Course outline
1
What is data engineering?
In this chapter, you’ll learn what data engineering is and why demand for them is increasing. You’ll then discover where data engineering sits in relation to the data science lifecycle, how data engineers differ from data scientists, and have an introduction to your first complete data pipeline.
2
Storing data
It’s time to talk about data storage—one of the main responsibilities for a data engineer. In this chapter, you’ll learn how data engineers manage different data structures, work in SQL—the programming language of choice for querying and storing data, and implement appropriate data storage solutions with data lakes and data warehouses.
3
Moving and processing data
Data engineers make life easy for data scientists by preparing raw data for analysis using different processing techniques at different steps. These steps need to be combined to create pipelines, which is when automation comes into play. Finally, data engineers use parallel and cloud computing to keep pipelines flowing smoothly.
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Understanding Data Engineering
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