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DANA-262: Analyzing with Cloudera Data Warehouse( Analyzing With Cloudera Data Warehouse ) Course Overview

DANA-262: Analyzing with Cloudera Data Warehouse( Analyzing With Cloudera Data Warehouse ) Course Overview

Embark on a transformative four-day journey with DANA-262: Analyzing with Cloudera Data Warehouse, a course designed for data analysts, business intelligence specialists, developers, and database administrators. Through expert instruction and practical, hands-on exercises, you will master the tools to effectively access, manipulate, and analyze big data using SQL and Scripting languages in CDP Public Cloud environments. Learn to optimize data queries with Apache Hive and Apache Impala, understand data storage solutions like HDFS, and handle complex data structures. This course equips you with skills to enhance decision-making processes, ensuring you can tackle modern data challenges efficiently.

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Target Audience for DANA-262: Analyzing with Cloudera Data Warehouse( Analyzing With Cloudera Data Warehouse )

DANA-262: Analyzing with Cloudera Data Warehouse is a four-day course ideal for professionals aiming to leverage big data using SQL and scripting languages.


Target Audience for DANA-262:


  • Data Analysts
  • Business Intelligence Specialists
  • Database Administrators
  • System Architects
  • Developers familiar with SQL
  • IT Professionals with basic Linux command-line skills


Learning Objectives - What you will Learn in this DANA-262: Analyzing with Cloudera Data Warehouse( Analyzing With Cloudera Data Warehouse )?

Introduction to the Course’s Learning Outcomes: The DANA-262 course equips participants with the skills to utilize Cloudera Data Warehouse for performing complex data analytics, using SQL and script languages through hands-on exercises.

Learning Objectives and Outcomes:

  • Understand and navigate the ecosystems of Apache Hive and Apache Impala.
  • Execute complex SQL queries involving functions, aggregate functions, and subqueries.
  • Apply joins and unions effectively to merge datasets.
  • Manage database entities such as tables, views, and databases including their creation, modification, and deletion.
  • Optimize data storage and retrieval using various file formats and partitioning schemes.
  • Leverage analytic and windowing functions to derive deeper insights from data.
  • Handle complex and nested data structures within Hive and Impala environments.
  • Improve query performance through optimization techniques specific to Hive and Impala.
  • Decide the appropriate data processing tools (Hive, Impala, RDBMS) based on the analytical needs.
  • Utilize CDP Public Cloud Data Warehouse features effectively for scaling and managing data solutions.

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