Course Description

This is a foundation level course designed to provide you with an understanding of Big Data, the potential sources of Big Data that can be used for solving real business problems and also provide an overview of Data Mining and the tools used in it. 

This is a fundamental course with practical exercises designed to provide you with some degree of hands-on experience in using two of the most popular technologies in Big Data processing – Hadoop and MongoDB. You will get the opportunity to practice installing these two technologies through our Work-Labs. The course exposes you to real-life Big Data technologies with the purpose of obtaining results from real datasets from Twitter.

After completing the course, you will be equipped not only with fundamental Big Data knowledge, but will also be introduced to a working development environment containing Hadoop and MongoDB, installed by yourself. This practical knowledge can be used as a starting point in the organizational Big Data journey.

Learning Objectives:

Individuals certified at this level will have demonstrated their understanding of:

  • Big Data fundamentals
  • Big Data technologies
  • Big Data governance
  • Available Sources of Big Data
  • Data Mining, its concepts and some of the tools used for Data Mining
  • Hadoop, including its concepts, how to install and configure it, the concepts behind MapReduce, and how Hadoop can be used in real life scenarios
  • MongoDB, including its concepts, how to install and configure it, the concepts behind document databases and how MongoDB can be used in real life scenarios

Benefits of taking this course:

Participants in this course will obtain the following benefits:

  • Detailed understanding of Big Data and Data Mining concepts.
  • Ability to identify and obtain relevant datasets when looking at a business problem.
  • Ability to install and manage Big Data processing environments based on Hadoop or MongoDB at a departmental level.


Exam Format: closed-book format. Paper-Based. Participants may bring paper-based dictionaries. No electronic devices are permitted.

Questions: 40 multiple choice questions

Passing Score: 65%

Exam Duration: 60 minutes. 15 minutes extra time for non-native English speakers

Proctoring: Web proctoring

Accreditation: Cloud Credential Council



2 days


Target Audience

This course is best suited to Information Technology professionals who possess intermediate to advanced programming, system administration or relational database skills and are looking to move into the area of Big Data. These include:

  • Software Engineers
  • Application Developers
  • IT architects
  • System administrators

The course can also be of benefit to other professionals, e.g. business, research, etc., who possess strong Information Technology skills and have a deep interest in Big Data analytics and the benefits it can bring to an organization.


Course Prerequisites

There are no formal prerequisites for this course.


Suggested Follow on Courses

There are various options of follow-on courses, depending on your business needs. Feel free to consult with us to see which course best suits you.


Course Content

Big Data Fundamentals

Big Data – History, Overview and Characteristics

  • History
  • Big Data Overview
  • Big Data Characteristics

Big Data Technologies – Overview

  • Hadoop
  • MongoDB

Big Data Success Stories

  • Target US
  • Fighting Piracy on High Seas

Big Data – Privacy and Ethics

  • Privacy
  • Ethics

Big Data Projects

  • WHO Should Be Involved?
  • What is Involved?

Big Data Sources

Enterprise Data Sources

  • Enterprise Systems
  • Data Warehouses
  • Unstructured Data

Social Media Data Sources

  • Facebook
  • Twitter
  • Other Social Media

Public Data Sources

  • Weather
  • Economics
  • Finance
  • Regulatory Bodies

Data Mining – Concepts and Tools

Data Mining – Introduction

  • Types of Data Mining

Data Mining – Tools

  • Weka
  • R Language

Big Data Technologies – Hadoop

Hadoop Fundamentals

  • Main Components of Hadoop
  • Additional Components of Hadoop

Install and Configure

  • Download
  • How to Install and Configure


  • How Does It Work?

Data Processing with Hadoop

  • Twitter Sentiment Analysis
  • Network Log Analysis

Practical Work

Big Data Technologies – MongoDB

MongoDB Fundamentals

  • Replication
  • Sharding
  • MongoDB Ecosystem

Install and Configure

  • Download
  • How to Install and Configure

Document Databases

  • Documents
  • Document Design Considerations
  • Fields

Data Modeling with Document Databases

  • Twitter Sentiment Analysis
  • Network Log Analysis

Practical Work



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