Foundations of Business Intelligence and Analytics
Course provided by Model Institute of Engineering & Technology
5 modules
Explore the fundamentals of Frontier Technologies
5 Level NCrF
National Credit Framework
60 Hours
Flexible Learning
Beginner Level
No prior experience required
Micro Credit Course
02 Credit
Course Overview
This course offers a comprehensive introduction to Business Intelligence (BI), equipping students with the skills to transform data into meaningful insights. It covers the fundamental concepts, benefits, and challenges of BI while exploring the broader BI ecosystem, including analytics workflows, ETL processes, and data repositories. Students will learn to apply statistical tools to uncover patterns, trends, and anomalies in data, and use BI tools to design impactful dashboards and reports. Emphasis is also placed on data storytelling techniques to help students effectively communicate their insights and support data-driven decision-making.
Key Learning Highlights
Grasp the core concepts, benefits, and challenges of Business Intelligence (BI)
Understand the BI ecosystem, including analytics workflows, ETL processes, and data repositories
Apply statistical tools to detect patterns, trends, and anomalies in data
Create impactful dashboards and reports using BI tools
Communicate insights effectively through data storytelling techniques
Tools & Platform Used
Learning Outcome
By the end of this course, students will be able to:
- Explain the key concepts, benefits, and challenges of Business Intelligence (BI)
- Describe the components of the BI ecosystem, including analytics workflows, ETL processes, and data repositories
- Apply statistical techniques to identify patterns, trends, and anomalies in datasets
- Develop interactive dashboards and reports using BI tools
- Present data-driven insights effectively through data storytelling techniques
Master the course with just 5 Modules
This course begins with an introduction to Business Intelligence (BI), covering its definition, evolution, key components, and differentiating it from data analytics and data science, along with an overview of roles and careers in BI. Learners then explore the data ecosystem and BI architecture, including structured and unstructured data, databases, data warehouses, data lakes, data pipelines, and cloud-based BI platforms. The course further delves into ETL and data preparation, focusing on extracting data from multiple sources, cleaning, transforming, and loading it efficiently while handling missing or noisy data. It then introduces statistical analysis and pattern discovery using descriptive statistics, correlation, and trend analysis to uncover insights that support decision-making. Finally, students learn data visualization and storytelling techniques to design impactful dashboards and reports, and communicate insights effectively to influence business decisions.
Introduction to Business Intelligence (BI)
- Understand the definition, evolution, and key components of BI systems
- Differentiate BI from data analytics and data science
- Explore various roles and career opportunities in the BI domain
Data Ecosystem and BI Architecture
- Learn about structured vs. unstructured data and their storage mechanisms
- Understand databases, data warehouses, and data lakes
- Explore data pipelines and cloud-based BI platforms
ETL and Data Preparation
- Study the ETL process for integrating data from multiple sources
- Practice data cleaning, transformation, and loading techniques
- Learn strategies for handling missing or noisy data
Statistical Analysis and Pattern Discovery
Apply descriptive statistics, correlation, and trend analysis
Use basic statistical tools available in BI platforms
Derive actionable insights to support data-driven decisions
Data Visualization and Storytelling
- Understand principles of effective data visualization
- Create interactive dashboards and reports
- Apply data storytelling techniques to communicate insights compellingly
Roles
Business Intelligence Analyst
Data Analyst
ETL Developer
BI Developer
Data Visualization Specialist
Data Engineer
Business Analyst
