Essentials of Data Analytics

Looking to improve your career?

In today's digital age, organizations need professionals with the skills to leverage data for growth, and this course will equip you with the analytical prowess to do just that. With a multi-dimensional approach to data literacy, you'll gain the expertise and confidence to lead successful digital initiatives and transform your organization. Enroll now and unlock the full potential of data for your career!

Course completion in 12 hours Certificate Provided
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Normal Price
USD 20

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USD 4.99

For a limited time only!

This course includes:

  • 139 lessons
  • 12 hours video
  • 1 year access
  • Certificate of completion
  • SIGNUP BONUS: FREE Access to over 6,000 upskilling contents
Buy NowOne-Time Payment

What you'll learn

Course completion in 8-81 hours

Learn about technologies, methodologies and frameworks of Big Data, Big Data Analytics.


Learn from real life use case on how Big Data Analytics insights can be used for competitive advantage.


Data Preparation: Start with the basics of Excel & discover how to prepare data for analysis.


Data Analysis: Learn how to use Excel with various statistical methods to analyze & make sense of your data.


Data Visualization: Learn how to create effective data visualizations, like powerful graphs to communicate insights like a pro.


Data Storytelling: Learn how to structure data & insights in presentations effectively & efficiently.


There are no advanced preparation or prerequisites needed.

About the Course

As digital transformation continues to reshape the business landscape, self-improvement through online learning has become essential for career success.

The Essentials of Data Analytics (EDP) program equips professionals with the skills to leverage data for growth, making it a must-have for anyone seeking a better career in the digital age. With a focus on business intelligence and data literacy, this course provides a multi-dimensional approach to data analysis that will keep you ahead of the curve. Develop your data and analytics skills with Excel and unlock your full potential.

Enroll in the EDP program now and stay competitive in the evolving job market.

Who this course is for

Anyone interested in Business Operations & Technology

Everyone & anyone from University Students to Working Professionals in today’s world

Course Content

Chapter 1: Fundamentals of Big Data Analytics - Introduction

Course Outline

What, Why and How of Big Data

Segments of Big Data

Growth of Big Data

Case Study - Coursera

Public Cloud in Big Data

The Challenges of Big Data Adaptation

Data Silos

Driving Factor in Big Data Investments

Primary Driver of Big Data in Companies



Chapter 2: Big Data Technologies


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

Analysis Layer

Consumption Layer

Analysis 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



Chapter 3: Managing Big Data - Software & Technology


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 Dril

Distance to Data

Evolution Towards Self-Service Data Exploration

Hadoops Vendors



Chapter 4: Big Data Analytics


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




Chapter 5: Use Cases









Chapter 6: Excel Fundamentals & Pivot Table


Welcome Notes

Learning Goals

Learning Contents

Fundamentals on Worksheet, Excel


Predefined Functions on Descriptive Statistics, Data Organisation, Conditionals, DateTime and Search Functions


Data Normalisation & Its Technique

Pivot Table, Its Functions & Applications


Chapter 7: Excel Visualization & Dashboard

Learning Contents

Conditional Formatting and Sparklines


Preparing Datasets for Visualization

Creating Effective Charts with Design Best Practices


Creating a PivotChart

Types of Dashboard and Their Functions


Checklist for Creating a Dashboard


Step by Step Guide to Dashboarding

Interacting with your Charts

Chapter 8: Exploratory Data Analysis with Excel

Progress so far

Learning Contents

Introduction to Statistical Data Analysis

One Categorical Variable - One Way Table & Pivot Table

One Categorical Variable - Pie Chart, Bar Chart & Application

One Numerical Variable - Central Tendency, Median, Mean, Mode & Application


One Numerical Variable - Dispersion, Variability, Range, Percentile, IQR, Outlier, Variance & Standard Deviation


One Numerical Variable - Boxplot, Histogram & Application

Examining Relationship - Two Categorical Variables (C->C) with Pivot Table


Examining Relationship - Two Categorical Variables (C->C) with Charts

One Categorical Variable & One Numerical Variable (C-Q) with Pivot Table & Charts


Examining Relationship - Two Numerical Variable (Q->Q) with Pivot Table

Examining Relationship - Two Numerical Variable (Q->Q) with Pearson’s Correlation Coefficient


Examining Relationship - Two Numerical Variable (Q->Q) with Charts

Excel Analytics Module Summary, Recap & Application

Chapter 9: Data Visualization for Business Intelligence with Excel


Welcome Notes & Learning Goals

Learning Contents

Excel Interface and Essentials

Types of Data


Steps to Create a Pivot Table

Steps to Create Bar Chart, Pie Chart and Line Chart with Time Series


Conditional Formatting & Its Techniques


Types of Dashboard and Their Functions

Chart Tools & Their Functions


Overall Summary, Recap & Application

Chapter 10: Data Storytelling - The Process of Effective Data Storytelling


Welcome Notes

Learning Goals

Learning Contents

Examples of Poor Storytelling


The Data Storytelling Process - Who


The Data Storytelling Process - What


The Data Storytelling Process - How




Chapter 11: Data Storytelling - Making Impactful Visual for Your Data Story

Welcome Back!

Learning Goals

Learning Contents

Graphical Perception


Choosing a Visual


Making a Visual from Good to Great


Overall Summary, Recap & Application

Here's what some of our past learners have to say:

“I highly recommend the Essentials of Data Analytics course to anyone looking to gain the skills and knowledge needed to succeed in data analytics.”

Adib Bakri

Exec, Policy & Operations,HRDF.

“The Essentials of Data Analytics course was exactly what I needed to advance my career in data analytics. The course content was relevant and practical.”

Alisa Yap

Red Sand Marine Sdn Bhd.

“The Essentials of Data Analytics course was an excellent investment in my career. The skills and knowledge I gained have helped me advance in my role as a data scientist.”

Muhammad Harun Bin Sharifudin




Frequently Asked Questions

Will I receive a certificate upon completing the course?

Yes, you will receive a certificate of completion upon finishing the course.

How long does the course take?

We've prepared approximately 12 hours of learning content for you, however it is a self-paced online course and you can complete it on your own time.

How long will the course be available for me to complete?

The course will remain in your learning library for 1 Year.

How do I make payment?

We accept payments from any visa/mastercard transactions.

How will the course help me advance in my career in data analytics?

The course will provide you with the skills and knowledge you need to become an expert in data analytics. You'll be able to apply these skills to your current job or use them to advance to a higher-level position in the field.

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