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!
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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.
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.
Everyone & anyone from University Students to Working Professionals in today’s world
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
Takeaways
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
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
Takeaways
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 Dril
Distance to Data
Evolution Towards Self-Service Data Exploration
Hadoops Vendors
Takeaways
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
Overview
Amex
Delta
Walmart
UPS
Alibaba
Ending
Introduction
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
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
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
Introduction
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
Introduction
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
Storyboarding
Welcome Back!
Learning Goals
Learning Contents
Graphical Perception
Choosing a Visual
Making a Visual from Good to Great
Overall Summary, Recap & Application
Adib Bakri
Exec, Policy & Operations,HRDF.
Alisa Yap
Red Sand Marine Sdn Bhd.
Muhammad Harun Bin Sharifudin
UMW
Yes, you will receive a certificate of completion upon finishing the course.
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.
The course will remain in your learning library for 1 Year.
We accept payments from any visa/mastercard transactions.
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.
Samsung Engineering, Kuala Lampur, Malaysia
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