This course provides a comprehensive introductory overview of the concept of Big Data, and its technologies, architectures, and management. Participants can reap the benefits of this course when planning Big Data projects, and understanding the technology involved using different types of analytics such as Descriptive Analytics, Predictive Analytics, and Machine Learning.

Complete in 4-7 hours. Get a certificate at the end of this course.

Foundation for Forward-Thinking Data-Driven Leaders

Knowledge is power. Be at the forefront of the known with Big Data Analytics 101.

Bridge the gap between your current capabilities and the skills needed to stay competitive.
data-driven, leaders

Plan for the next decade of growth

Nearly 80% of organizations that adopt data analytics and AI experience a boost in data insight, sales, operational efficiency, and, most importantly, customer satisfaction.

  • Drive Business Growth

    Learn how major organizations use big data analytics to inform strategic and operational decisions for future growth

  • Unlock Business Value

    Learn how big data analytics get the maximum value from your data by extracting strategic and actionable insights through analysis

  • Lead Business Transformation

    The future belongs to Data-Driven Leaders who are able to transform data into strategic business decisions, value-driven products, and lead predictions.

Course curriculum

  • 1

    Chapter 1: Introduction

  • 2

    Chapter 2: Big Data Technologies

    • Chapter 2 Overview

    • Requirements of Big Data Architecture

    • Converting Raw Data into Insight

    • Establishing the Architectural Foundation

    • Defining Big Data Architecture

    • Evaluation Criteria Before Investing in Big Data Solution

    • Asking the Right Questions to Start Big Data Project

    • Logical Layers of Big Data

    • Big Data Sources

    • Data Massaging and Store Layer

    • Analysis Layer

    • Consumption Layer

    • Big Data Reference Architecture

    • Physical & Security Infrastructure

    • Shared Infrastructure

    • Resiliency and Redundancy

    • Security Infrastructure

    • Operational Database

    • Non-Relational Databases

    • SQL & NoSQL Database Engines

    • How Data Lakes Work

    • Extract Transform Load

    • Analytical Data Warehouse

    • Data Warehouse vs Data Lake

    • Importance of Big Data Analytics

    • Types of Visualisation Tools

    • The Cloud's Role in Big Data

    • Why The Cloud is Important for Big Data

    • Defining Cloud Computing in Big Data

    • Two Types of Cloud Model in Big Data

    • Cloud Deployment Model

    • Cloud Delivery Model

    • Using The Cloud in Big Data

    • Takeaways

    • Chapter 2 Quiz

  • 3

    Chapter 3: Managing Big Data - Software & Technology

    • Chapter 3 Overview

    • Defining Big Data

    • The Datafication of Our World

    • Understanding Big Data & The 3 Vs of Big Data

    • Big Data Technologies

    • The Hadoop Story

    • Technologies in Hadoop Ecosystem

    • Hadoop HDFS

    • Hadoop MapReduce

    • Apache Spark

    • HDFS vs Spark

    • Apache Drill

    • Data Preparation

    • Clients Support for Drill

    • Datastores Supported by Drill

    • Distance to Data

    • Evolution Towards Self-Service Data Exploration

    • Hadoop Vendors

    • Takeaways

    • Chapter 3 Quiz

  • 4

    Chapter 4: Big Data Analytics

    • Chapter 4 Overview

    • Big Data Analytics

    • Types of Data Analytics

    • Reasons Organisations Deploy Big Data Analytics

    • Implementing a Big Data Analytics Solution

    • Big Data Analytics Summary

    • Big Data Analytics Process Flow

    • How Big Data Analytics Are Being Used

    • Basic Analytics

    • Advanced Analytics for Insight

    • Operationalised Analytics

    • Monetising Analytics

    • Big Data Analytics Solutions

    • Machine Learning in Hadoop Ecosystem

    • Machine Learning - Apache Mahout™

    • Spark MLlib

    • Flink

    • Takeaways

    • Chapter 4 Quiz

  • 5

    Chapter 5: Use Cases

  • 6

    Final Assessment

    • Final Assessment

    • Course Feedback


Eye-opening use cases


The most interesting thing that I learned from this training program is how the companies and industries adopt Big Data Analytics to improve their services, increase their revenues and save cost as shown in Chapter 5: Use Cases. This provides more insights and motivations for me to adopt what I had learned into my future works.

Unlock hidden value of data

Muhammad Abdurrahman Tabrani

Thank you very much. I have benefited a lot from this training course. I hope to enroll for more in the future. I can understand better how organizations use data they gain for their own good and get insight into how to improve business operation using data analytics.

Insightful and memorable

Bin Xuan Kong

An insightful, comprehensive look at Big Data Analytics, a memorable learning experience. I gain a deeper understanding and overview of Big Data Analytics and its structure that is applicable to different industries.

Enlightening course for me

Tharuma Rajah

Very enlightening for non-data science professionals.

So much to learn

Muhamad Danial Akif

It has been a wonderful experience in online learning for about only 3 hours and can be manageable following my own pace of learning. It was quite a fast learning course however I was able to understand, Alhamdulillah. From there, I learned a lot about big data, the key terms of innovation of it, types of big data, examples of the company used, type of database software used, and much more. Thank you once again for this opportunity.