Unit 5.7
An Introduction to Business Intelligence (BI)
IT 231: IT and Application
Learning Objectives 🎯
By the end of this chapter, you will be able to:
- ✅ Define Business Intelligence (BI).
- ✅ Describe the purpose of BI.
- ✅ Identify the key technologies used in BI.
What is Business Intelligence (BI)?
Business Intelligence (BI) is a technology-driven process for analyzing data and presenting actionable information to help executives, managers, and other corporate end-users make informed business decisions.
In simple terms: BI turns raw data into useful insights. ⚡
The Core Purpose of BI
BI exists to support better business decision-making.
The goal is not just to collect data, but to understand it and use it to drive strategy and performance.
It helps answer questions like:
- What were our sales last quarter?
- Which products are most profitable?
- How can we improve operational efficiency?
The BI Process: From Data to Decisions
📊 Raw Data
(Sales figures, customer records, web traffic)
⬇️
⚙️ BI System
(Collection, Integration, Analysis)
⬇️
💡 Actionable Information
(Reports, Dashboards, Visualizations)
Raw Data vs. Actionable Information
Raw Data बिखरा डेटा
- Unorganized facts and figures.
- Example: A list of 10,000 individual sales transactions.
- Difficult to understand context or trends.
Actionable Information ⚡
- Organized, analyzed data.
- Example: A chart showing "Total Sales per Region for Q3".
- Provides clear insights to make decisions.
Key BI Technologies 🔍
A successful BI system relies on several core components working together:
- Data Warehouses: The foundation for storing data.
- ETL Processes: The "plumbing" that moves data.
- Reporting & Querying Tools: For asking questions.
- Data Visualization & Dashboards: For understanding the answers.
Component 1: Data Warehouse
A Data Warehouse is a central repository of integrated data from one or more disparate sources.
- Stores clean, consolidated, and historical data.
- Designed specifically for querying and analysis.
- It's the single source of truth for an organization's data.
Think of it as a highly organized library for all your business data.
Component 2: ETL Process
Extract, Transform, Load
1. Extract
Pulling data from various sources (databases, CRM, files).
2. Transform
Cleaning, standardizing, and structuring the data.
3. Load
Loading the transformed data into the data warehouse.
ETL is the critical background process that ensures the data in the warehouse is reliable and ready for analysis.
Component 3 & 4: Analysis and Visualization
Reporting & Querying
- Allows users to ask specific questions of the data (e.g., using SQL).
- Generates static reports (PDFs, spreadsheets).
- Answers "What happened?"
Data Visualization & Dashboards
- Tools like Tableau & Power BI.
- Creates interactive charts, graphs, and maps.
- Helps users explore data visually and answer "Why did it happen?"
Practical Application: BI in Nepal
Scenario: A Nepali Telecom Company 🇳🇵
A company like Ncell or Nepal Telecom collects massive amounts of data:
- Call records, data usage, recharge card purchases, customer location.
How can they use BI?
- Marketing: A dashboard shows that data usage in Pokhara peaks between 8-10 PM. They can create a targeted "Night Data Pack" for that region.
- Network Ops: A report identifies areas with frequent call drops, helping engineers prioritize tower maintenance and upgrades.
Summary & Key Takeaways
- 🎯 BI is the process of turning raw data into actionable insights to support better business decisions.
- ⚙️ It transforms messy, raw data into clean, understandable information like reports and dashboards.
- 🏗️ Key components include a Data Warehouse for storage and Visualization Tools (like Power BI) for presentation.
- ⚡ The ultimate goal of BI is to improve business performance by making data-driven choices.