This course on Apache Hive provides a comprehensive overview of big data warehousing and analytics using one of the most widely adopted tools in the Hadoop ecosystem. The course spans data engineering, business intelligence, enterprise analytics, and large-scale data processing, covering the fundamentals of HiveQL, strategies to design efficient data warehouse schemas, approaches to optimize query performance, and methods to manage and analyze massive datasets with reliability and scale. In this course, you will learn from industry experts who have more than 15 years of experince in big data.
Prerequisites
- Basic understanding of databases and SQL.
- Understanding of Hadoop ecosystem
- Knowledge of Linux command-line operations.
- Basic programming skills (Java/Python)
What Will You Learn
- Introduction to Apache Hive
- Hive Architecture and Components
- Hive Installation and Configuration
- Hive Data Types
- Creating Databases and Tables
- Managed vs External Tables
- Partitioning and Bucketing
- Loading and Querying Data
- Updating and Deleting Data
- HiveQL Queries and Joins
- Subqueries and Views
- User Defined Functions (UDFs)
- Performance Optimization and Tuning
- Integration with HBase, Sqoop, and Flume
- Security, Authorization, and Data Governance