FAQ

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.

Purchase This Course

Fee On Request

  • Live Training (Duration : 32 Hours)
  • Per Participant
  • Guaranteed-to-Run (GTR)
  • Classroom Training fee on request
  • Select Date
    date-img
  • CST(united states) date-img

Select Time


♱ Excluding VAT/GST

You can request classroom training in any city on any date by Requesting More Information

Inclusions in Koenig's Learning Stack may vary as per policies of OEMs

  • Live Training (Duration : 32 Hours)
Koeing Learning Stack

Koenig Learning Stack

Free Pre-requisite Training

Join a free session to assess your readiness for the course. This session will help you understand the course structure and evaluate your current knowledge level to start with confidence.

Assessments (Qubits)

Take assessments to measure your progress clearly. Koenig's Qubits assessments identify your strengths and areas for improvement, helping you focus effectively on your learning goals.

Post Training Reports

Receive comprehensive post-training reports summarizing your performance. These reports offer clear feedback and recommendations to help you confidently take the next steps in your learning journey.

Class Recordings

Get access to class recordings anytime. These recordings let you revisit key concepts and ensure you never miss important details, supporting your learning even after class ends.

Free Lab Extensions

Extend your lab time at no extra cost. With free lab extensions, you get additional practice to sharpen your skills, ensuring thorough understanding and mastery of practical tasks.

Free Revision Classes

Join our free revision classes to reinforce your learning. These classes revisit important topics, clarify doubts, and help solidify your understanding for better training outcomes.

Inclusions in Koenig's Learning Stack may vary as per policies of OEMs

Scroll to view more course dates

♱ Excluding VAT/GST

You can request classroom training in any city on any date by Requesting More Information

Inclusions in Koenig's Learning Stack may vary as per policies of OEMs

Request More Information

Email:  WhatsApp:

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.

Suggested Courses

What other information would you like to see on this page?
USD