Introduction to Data Engineering is the first module of the course that provides an overview of the field of data engineering. It includes the following topics:
What is Data Engineering: This section defines what data engineering is and its role in the larger field of data science and analytics. It also explains the difference between data engineering and other related fields such as data warehousing and data integration.
Importance of Data Engineering: This section covers the importance of data engineering in today's data-driven world and the various industries where data engineering plays a critical role.
Areas of focus within Data Engineering: This section explores the different areas of focus within data engineering, such as data warehousing, data integration, big data, and data governance.
Data Engineering Tools and Technologies: This section covers the various tools and technologies used in data engineering such as SQL, Hadoop, Spark, and Cloud computing platforms.
Data Engineering Methodologies: This section covers the different methodologies used in data engineering such as Agile and Waterfall.
Real-world Applications: This section provides examples of real-world applications of data engineering to give students a better understanding of the concepts covered in the module.
Summary: This section provides a summary of the key concepts covered in the module and what students should have learned.
The module is designed to give students a broad understanding of the field of data engineering and its importance in today's data-driven world.
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