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Course Description
What to Expect From Cloudera Data Analyst
Through instructor-led discussion and interactive, hands-on exercises, participants will navigate the ecosystem, learning:
- How the open-source ecosystem of big data tools addresses challenges not met by traditional RDBMSs
- Using Apache Hive and Apache Impala to provide SQL access to data
- Hive and Impala syntax and data formats, including functions and subqueries
- Create, modify, and delete tables, views, and databases; load data; and store results of queries
- Create and use partitions and different file formats
- Combining two or more datasets using JOIN or UNION, as appropriate
- What analytic and windowing functions are, and how to use them
- Store and query complex or nested data structures
- Process and analyze semi-structured and unstructured data
- Techniques for optimizing Hive and Impala queries
- Extending the capabilities of Hive and Impala using parameters, custom file formats and SerDes, and external scripts
- How to determine whether Hive, Impala, an RDBMS, or a mix of these is best for a given task