Data Definition and Manipulation Languages: Views

Related lectures (24)

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Introduces the relational model and algebra, essential for understanding data-intensive systems and effective database management.

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

Explores how views simplify query writing and are key in data warehouses.

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

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

Covers data wrangling techniques using Hadoop, focusing on row versus column-oriented databases, popular storage formats, and HBase-Hive integration.

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

Explores Apache Hive for data warehousing, data formats, and partitioning, with practical exercises in querying and connecting to Hive.

Explores data warehouses, decision support systems, OLAP, data lakes, multidimensional data models, and query optimizations.

Introduces fundamental concepts of data management, including data models, databases, and key tasks.