Business Analytics

Course Duration: 32 Hours of Comprehensive Learning

Mode of Learning:

Choose the learning style that best fits your schedule and preferences:

Online Instructor-Led Training – Learn in real time with live expert-led sessions.
Online Self-Paced Learning – Study anytime, anywhere with flexible recorded modules.
Onsite/Classroom Training – Experience in-person, hands-on learning guided by certified trainers.

What’s Included in the Training Program:

Our industry-leading Training Program is designed to provide a complete learning experience through a perfect blend of theory and practical exposure. Here’s what you’ll get:

Live, Instructor-Led Online Training Sessions
Hands-on Lab Exercises
Certified and Experienced Trainers
Post-Training Support & Mentorship
Comprehensive Learning Resources including eBooks, guides, and reference materials.
Real-World Case Studies & Application Scenarios
Networking Opportunities
Group Projects and Collaborative Learning Activities
Best Practices and Industry Insights.
Access to Recorded Sessions (available for online learners, based on client permissions).
Follow-up Review Sessions.
Tool Demonstrations and Guided Walkthroughs

This training helps you gain the knowledge and hands-on experience needed to advance your career in today’s competitive IT landscape.

Course Content

What is Business Analytics?

Importance and Types of Business Analytics
Role in Decision-Making

Overview of Business Analytics Tools

Data Collection Methods

Data Cleaning Fundamentals

Understanding EDA

Practical EDA with R and Tableau

Central Tendency and Dispersion

Data Visualization for Descriptive Statistics

Getting Started with Power BI

Creating Basic Visualizations

Power BI Advanced Visuals

Data Transformation in Power BI

Getting Started with Tableau

Basic Visualizations in Tableau

Advanced Tableau Features

Data Storytelling Using Tableau

What is Predictive Analytics?

Using R for Predictive Analytics

Overview of Machine Learning

Basic Machine Learning Algorithms

Using Analytics for Informed Decisions

Optimizing Business Outcomes Using Analytics

Practical Application of Predictive Analytics

Evaluating Predictive Model Performance

Applying Business Analytics to Case Studies

Collaborative Problem Solving

Advanced Features in Power BI and Tableau

Analytics Automation Using R

Project Work

Preparing Reports and Dashboards

Review of Key Concepts

Next Steps

Course Duration: 32 Hours of Comprehensive Learning

Mode of Learning:

What’s Included in the Training Program:

Course Content

What is Business Analytics?

Importance and Types of Business Analytics

Role in Decision-Making

Overview of Business Analytics Tools

Tools for Business Analytics: R, Tableau, Power BI

Introduction to Data Analytics Lifecycle

Data Collection Methods

Sources of Business Data

Best Practices for Data Collection

Data Cleaning Fundamentals

Handling Missing Data, Outliers, and Duplicates

Tools for Data Cleaning (Excel, R)

Understanding EDA

Techniques for Summarizing Data

Identifying Trends and Patterns

Practical EDA with R and Tableau

Visualizing Data with R and Tableau

Uncovering Insights from Data

Central Tendency and Dispersion

Measures: Mean, Median, Mode, Variance

Data Visualization for Descriptive Statistics

Creating Visuals in Tableau and Power BI

Getting Started with Power BI

Overview of Power BI Interface

Connecting Data Sources to Power BI

Creating Basic Visualizations

Bar Charts, Line Graphs, Pie Charts

Power BI Advanced Visuals

Creating Dashboards and Interactive Reports

Data Transformation in Power BI

Power Query Editor

Data Modeling Techniques

Getting Started with Tableau

Overview of Tableau Interface

Connecting and Preparing Data

Basic Visualizations in Tableau

Creating Graphs and Charts

Advanced Tableau Features

Building Interactive Dashboards

Data Storytelling Using Tableau

Creating Insightful Visuals for Stakeholders

What is Predictive Analytics?

Types of Predictive Models: Regression, Classification

Using R for Predictive Analytics

Implementing Basic Regression Models in R

Overview of Machine Learning

Types of Machine Learning: Supervised and Unsupervised

Applications of Machine Learning in Business Analytics

Basic Machine Learning Algorithms

Classification and Regression with R

Using Analytics for Informed Decisions

Data-Driven Decision-Making Process

Optimizing Business Outcomes Using Analytics

Decision-Making Models and Techniques

Practical Application of Predictive Analytics

Real-World Case Study: Business Use of Predictive Models

Evaluating Predictive Model Performance

Model Accuracy and Evaluation Techniques

Applying Business Analytics to Case Studies

Solving Business Problems Using Power BI, Tableau, and R

Collaborative Problem Solving

Group Work on Real-Life Business Analytics Challenges

Advanced Features in Power BI and Tableau

Customizing Visualizations

Complex Data Transformation in Power BI

Analytics Automation Using R

Automating Data Analysis Processes in R

Project Work

Students apply Power BI, Tableau, and R to a Business Analytics Problem

Preparing Reports and Dashboards

Creating and Presenting Findings from the Final Project

Review of Key Concepts

Recap of Business Analytics Tools and Techniques

Next Steps

Preparing for Business Analytics Careers