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This lecture covers the use of Apache Hive as a data warehouse for managing large datasets, including data formats, data wrangling, and partitioning. Topics include HiveQL, schema on read, data storage, partitioning, and Hive under the hood. The lecture also explores popular HDFS storage formats, Hive equivalents in cloud solutions, and the differences between HDFS and Hive. Practical exercises involve creating external tables, querying data, and connecting to Hive using PyHive.