Managing Big Data Operations


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


Overview/Description
This course covers the types of challenges being faced day to day by rethinking data systems from the ground up. This course also covers in-depth topics such as monitoring tools, orchestrations, and performance modeling.

Target Audience
Project managers, Business Intelligence or ETL developers, data architects, data analysts and big data enthusiasts interested in a higher comprehension of big data; some knowledge of big data or data science, data warehouse, ETL, or any of the applications/software used in the industry today would be ideal

Prerequisites
None

Expected Duration (hours)
0.7

Lesson Objectives

Managing Big Data Operations

  • start the course
  • describe big data and where it's heading today
  • recognize the trends and the various industries that are exposed to big data operations
  • identify the technologies and advancements in big data
  • describe the process of monitoring big data repositories and predictive modeling
  • recognize the various big data KPIs and how each can be used
  • describe the various performance issues and how to solve them using data monitoring
  • recognize big data network monitoring operations and its importance
  • list the various software and applications that can be used to provide big data orchestrations
  • recognize the operations that integrate big data
  • recognize the various processes of automating ETL jobs
  • describe big data trends and characteristics

    • Course Number:
    df_bdop_a01_it_enus

    Expertise Level
    Intermediate