Fundamentals of BigData Course

Welcome to Fundamentals of BigData Online Course with live Instructor using an interactive cloud desktop environment DaDesktop. Experience remote live training using an interactive, remote desktop led by a human being!

7 hours


What is BigData?

Big data is a generic term given to datasets that are so large or complicated that they are difficult to store, manipulate and analyse. The three main features of big data are:

  • volume: the sheer amount of data is on a very large scale
  • variety: the type of data being collected is wide-ranging, varied and may be difficult to classify.
  • velocity: the data changes quickly and may include constantly changing data sources.

The lack of structure in Big Data is considered to be the aspect creating the most difficulties. For this reason, traditional data analysis and organisation methods such as relational databases or SQL are no longer useful when it comes to Big Data . However, when the correct techniques are applied to Big Data, a vast amount of useful information can be revealed. Processing Big Data allows professionals such data scientists to spot and analyse hidden patterns and relationships which wouldn't have been easy to interpret before.

Big data is used for different purposes. In some cases, it is used to record factual data such as banking transactions. However, it is increasingly being used to analyse trends and try to make predictions based on relationships and correlations within the data. Big data is being created all the time in many different areas of life. Examples include:

  • scientific research
  • retail
  • banking
  • government
  • mobile networks
  • security
  • real-time applications
  • the Internet.


  • Definition
  • Characteristics
  • Architecture
  • Technologies
  • Applications

Course Category:

   Big Data Training

Last Updated:


Course Schedules

Date Time
June 15, 2023 (Thursday) 09:30 AM - 04:30 PM
June 29, 2023 (Thursday) 09:30 AM - 04:30 PM
July 13, 2023 (Thursday) 09:30 AM - 04:30 PM
July 27, 2023 (Thursday) 09:30 AM - 04:30 PM
August 10, 2023 (Thursday) 09:30 AM - 04:30 PM
August 24, 2023 (Thursday) 09:30 AM - 04:30 PM
September 7, 2023 (Thursday) 09:30 AM - 04:30 PM

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