Overview
Analytics Engineering is the bridge between data science and data analytics. It focuses on building and maintaining data pipelines, ensuring data quality, and making data accessible for analysis. This field combines programming, data modeling, and business understanding to help organizations make data-driven decisions. In this introduction, students will learn the fundamentals of analytics engineering and its importance in the data landscape.
📚 Key Learning Objectives
- ✓ Define key concepts of analytics engineering.
- ✓ Identify the role of data pipelines in analytics.
- ✓ Explain the importance of data quality.
- ✓ Describe tools used in analytics engineering.
- ✓ Apply basic data modeling techniques.
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