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Introduction to Data Modeling in Hadoop


Overview/Description
Target Audience
Prerequisites
Expected Duration
Lesson Objectives
Course Number


Overview/Description
This course covers various data genres and management tools, the reasons behind the evolving plethora of new big data platforms from the perspective of big data management systems, and analytical tools.

Target Audience
Individuals who are new to big data, Hadoop, and data modeling, and wish to understand key concepts and features of Hadoop and its tools

Prerequisites
None

Expected Duration (hours)
1.1

Lesson Objectives

Introduction to Data Modeling in Hadoop

  • start the course
  • define data management
  • recognize important data modeling concepts in Hadoop
  • identify important issues for storing data in Hadoop
  • recognize important considerations when designing HDFS schema
  • recognize important points when designing HDFS schema
  • identify basic concepts of data movement in Hadoop
  • list important factors that need to be considered for importing data into Hadoop
  • identify tools and methods for moving data into Hadoop
  • recognize characteristics of a data stream
  • define how data lakes enable batch processing
  • define data security management and its major domains
  • define Kerberos
  • define basics of authentication in Hadoop using Kerberos
  • identify central issues in processing and management of big data
  • identify important points in Hadoop data modeling
  • Course Number:
    df_dmhp_a02_it_enus