Data-Intensive Systems: Relational Model and Algebra

Related lectures (32)

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Covers the architecture of a typical DBMS and SQL interfaces like SQL Developer and DataGrip.

Explores relational algebra equivalences for optimizing query performance through efficient tuple generation and join operations.

Covers the fundamentals of data, cloud storage, and the Internet of Things.

Introduces the fundamentals of handling data, emphasizing the importance of Pandas and data modeling for effective analysis.

Introduces the Entity-Relationship model for designing databases with a focus on conceptual and relational aspects.

Covers the fundamentals of DBMS, relational algebra operators, and their importance in managing large datasets.

Introduces data modeling concepts, SQL usage, and Pandas library applications for efficient data processing.

Explores query processing steps, physical plans, pipelined execution, and hashing for projections and joins.

Covers relational query optimization, including logical and physical query plans, cost estimation, equivalences, and the System R strategy.

Explores data wrangling with Hadoop, emphasizing storage formats and Hive for big data processing.