Big Data Training: Fundamentals

Course Description

This 3-day course is designed to give you a better understanding of Big Data topics focusing on Hadoop. It covers ins and outs of Big Data to clarify is it a buzzword, catch-phrase or something useful in our/your daily business. Also, it describes when we are considering something to be Big Data system, how architecture of typical Big Data system looks, what is ecosystem and who key players within Big Data space are? Is it related to data volume or technology in background? Does it replace existing technologies or is it enhancing them in joint existence? It will cover how to implement Hadoop jobs to extract business value from large and varied data sets, how to develop queries to simplify data analysis (with Pig, Hive, Cassandra and Impala).

Course Summary

Next Public Course Dates

UK & Europe:

  • 3 - 5 October 2023
  • 17 - 19 October 2023
  • 7 - 9 November 2023

US & Canada:

  • 26 - 28 September 2023
  • 10 - 12 October 2023
  • 24 - 26 October 2023
Prerequisites
  • None
Duration
  • 3 Days
Available Formats
  • Public Virtual Live Instructor-Led
  • Private Virtual Live Instructor-Led
  • Private Onsite
Audience
  • Anyone who wants overview of the key components for Big Data environment and broader Hadoop ecosystem

Course Modules

  • Introduction to Big Data (definition through 3V, 4V, 6V…)
  • Hadoop overview and Ecosystem
  • Delivering business benefit from Big Data
  • Integrating Big Data with traditional data
  • Storing & analyzing data in Big Data environment
  • Overview of Big Data stores and Data models: key value, graph, document, column-family
  • Deep dive into storage components: HDFS, HBase, Hive, Cassandra and Impala
  • Use Cases of different storage component
  • Comparing selected Big Data storage components to Traditional Databases
  • Relational Data Analysis within Big Data platform
  • Limitations and Future Directions for storage components

Upcoming Public Virtual Live Instructor-led Course Dates

UK & Europe:

US & Canada:


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