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Berkeley Global
Data Warehousing and Business Intelligence (BI) will explore the concepts, frameworks, and best practices for designing on-premises and cloud-based data warehousing solutions and explore how to use analytical tools to perform data analysis. The first few sections of the course will provide an understanding of data modeling, data warehousing, and SQL. The next few sections will provide an overview of the field of cloud computing, and its main concepts by utilizing cloud computing platforms. The last few sections of the course will examine data preparation, modeling, and data analytics using industry reporting tools, and/or Python-based machine learning libraries and Pandas DataFrame.
Prerequisites:
Basic understanding of SQL and relational databases.
Learner Outcomes
After successfully completing this course, you will be able to:
- Implement data modeling with multiple entities and relationships.
- Demonstrate the fundamental concepts of Database Management systems.
- Implement data warehousing techniques on-premises and on cloud platforms (e.g., MS Azure).
- Write queries to manage data, test, and optimize query performance.
- Use and create BI application (e.g., Power BI) to perform data analysis and visualization tasks.
- Perform data manipulation exercises using Python libraries and Pandas functions.
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Sections
Spring 2025 enrollment opens on October 21!