Cloudera Certified Associate (CCA) Data Analyst

Course CodeIT00041

Available Dates & Locations

This course is available in multiple locations and online. Choose the most suitable date and delivery method.

Dubai

Dates

Dubai

Venue / Hotel

Sheikh Zayed Rd Near Financial Metro Station - Dubai - United Arab Emirates

Hotel Website
Duration
2 Weeks
Price
€7,700
Cairo

Dates

Cairo

Venue / Hotel

22 El Messaha Sq.، Ad Doqi, Giza, Giza Governorate, Egypt

Duration
2 Weeks
Price
€5,775
Kuala Lumpur

Dates

Kuala Lumpur

Venue / Hotel

-

Duration
2 Weeks
Price
€9,450

Course Overview

This Certified Associate (CCA) Data Analyst Training course will teach you to apply traditional data analytics and business intelligence skills to big data. This course presents the tools data professionals need to access, manipulate, transform, and analyze complex data sets using SQL and familiar scripting languages. Advance Your Ecosystem Expertise Apache Hive makes transformation and analysis of complex, multi-structured data scalable in Cloudera environments. Apache Impala enables real-time interactive analysis of the data stored in Hadoop using a native SQL environment. Together, they make multi-structured data accessible to analysts, database administrators, and others without Java programming expertise.

Course Objectives

Throughout this training course participants will get to know:

  • 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 dierent 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?

Who Should Attend

This course is designed for:

  • Data analysts
  • Business intelligence specialists
  • Developers
  • Aystem architects
  • Database administrators

Course Outline

  • The Motivation for Hadoop
  • Hadoop Overview
  • Data Storage: HDFS Distributed Data Processing: YARN, MapReduce, and Spark
  • Data Processing and Analysis: Hive, and Impala
  • Database Integration: Sqoop _Other Hadoop Data Tools
  • Exercise Scenario Explanation