Data Streams and Approximation

Related lectures (32)

Page 1 of 4

Covers data streams, real-time analytics, challenges, data stream model, and efficient management.

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

Covers the basics of database systems, including data modeling, DBMS, data independence, and the course overview.

Introduces the relational model, SQL, keys, integrity constraints, ER translation, weak entities, ISA hierarchies, and SQL vs. noSQL.

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

Introduces the relational model and relational algebra, focusing on SQL and its operations for effective database management.

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

Covers data wrangling techniques using Apache Hive for efficient big data management.

Discusses query optimization in database systems, emphasizing the impact on performance and the decisions involved in improving database performance.

Covers query fusion, nested queries, and SQL operators in a geographical context.