Data Engineering: SQL, Python, Unix, Spark, Cloud, AWS, ETL, Data Quality , Data Governance & Data Architecture
Sub Category
- IT Certifications
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Objectives
- Hands on Python, SQL, Unix, Hadoop, Spark, CICD, ETL using IDE to replicate real life data engineering workflow
- Design, build, and manage scalable data pipelines using tools like Spark and frameworks for job orchestration, ensuring efficient data flow from ingestion to co
- Model data warehouses/lakes using star/snowflake schemas and optimize storage for analytics.
- Enforce data governance with quality checks, metadata management, and compliance frameworks
- Master advanced SQL for complex queries, ETL transformations, and database optimization.
- Troubleshoot pipelines using logging, monitoring tools, and error-handling strategies.
- Leverage cloud tools (AWS EC2, S3,Lambda) for cost-effective, auto-scaling data workflows.
- Identify real world problem statement, design and implement data pipeline.
Pre Requisites
- Basic Programming Knowledge
- No Prior Data Engineering Experience Needed
- Access to a Computer & Internet
- Curiosity about data workflows, databases, or cloud tools.
FAQ
- Q. How long do I have access to the course materials?
- A. You can view and review the lecture materials indefinitely, like an on-demand channel.
- Q. Can I take my courses with me wherever I go?
- A. Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
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