In this course, you will explore various types of source systems, learn how they generate and update data, and troubleshoot common issues you might encounter when trying to connect to these systems in the real world. You’ll dive into the details of common ingestion patterns and implement batch and streaming pipelines. You’ll automate and orchestrate your data pipelines using infrastructure as code and pipelines as code tools. You’ll also explore AWS and open source tools for monitoring your data systems and data quality.
Source Systems, Data Ingestion, and Pipelines
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Source Systems, Data Ingestion, and Pipelines
This course is part of DeepLearning.AI Data Engineering Professional Certificate


Instructors: Joe Reis
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Gain insight into a topic and learn the fundamentals.
Intermediate level
Recommended experience
3 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Gather stakeholder needs and translate them into system requirements.
Implement a batch and a streaming ingestion process on AWS to ingest data from various source systems.
Integrate aspects of security, data management, DataOps and orchestration into the data systems you build.
Skills you'll gain
Tools you'll learn
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Assessments
4 assignments
Taught in English
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This course is part of the DeepLearning.AI Data Engineering Professional Certificate
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There are 4 modules in this course
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