MSDS 420-DL Database Systems.

This course introduces data management and database systems with a focus on applications in large-scale analytics projects utilizing relational, document, vector, and graph-relational databases. Students learn about the relational model, the normalization process, and query languages, including Structured Query Language (SQL). They learn about data types, data models, and database programming for extract, transform, and load operations in databases. Students work with unstructured data, indexing and scoring documents for effective and relevant responses to user queries. They work with multiple database models housing different types of data, harnessing each model’s unique strengths to achieve a more comprehensive approach to data analysis. Recommended prior programming experience, MSDS 430-DL Python for Data Science, or MSDS 431-DL Data Engineering with Go. Prerequisites: None.

Students benefit by taking the SQL Learning Studio, Python Learning Studio, MSDS 430 Python for Data Science, and MSDS 431 Data Engineering with Go prior to taking this course.

Database systems and query languages in this course:

• Relational databases: PostgreSQL with Structure Query Language (SQL)
• Document stores: Elasticsearch, indexing, and natural language queries
• Vector databases: milvus for scalable similarity search
• Graph-relational databases: EdgeDB with EdgeQL and GraphQL

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