DI05000161 · Semester 5 · 5G scheme
Business Analytics
Notes and solutions following the Gujarat Technological University (GTU) syllabus for DI05000161. Independent material — not issued by the university.
Computer EngineeringComputer Science & Engineering
Materials
Syllabus units
Unit 1: Fundamentals of Business Analytics
- Introduction to Business Analytics
- Evolution of Business Analytics
- Business Analytics vs Data Analytics vs Data Science
- Types of Analytics: Descriptive, Diagnostic, Predictive, Prescriptive
- Business Analytics Lifecycle
- Components of Business Analytics System
- Applications of Business Analytics in Banking, Retail, Healthcare, and E-commerce
Unit 2: Business Data and Data Management
- Types of Data: Structured, Semi-structured, Unstructured
- Sources of Business Data: Internal Data Sources (sales records, customer databases, transaction data, ERP systems), External Data Sources (market research, social media, government datasets, third-party data)
- Data Collection Methods: Surveys and questionnaires, Observations, Transaction/Financial records, Online data sources (Social media platforms, E-commerce websites, Government open data portals, Web analytics tools, Online survey platforms), Sensors (IoT devices, RFID systems, GPS trackers, Smart meters, Wearable devices)
- Data Quality Issues in Business Data: Missing data, Duplicate data, Inconsistent data, Inaccurate data
- Data Cleaning and Data Preparation techniques: Handling missing data (deletion, imputation), removing duplicate records, handling inconsistent data (standardization, validation rules), data filtering and sorting, data type correction and formatting, outlier detection and treatment, data normalization and scaling, data encoding (categorical to numerical)
- Data Transformation and Data Integration techniques: Data aggregation and summarization, data normalization and standardization, data discretization (binning), feature construction and transformation, data merging and joining (multiple sources)
- Concept of Big Data in Business Analytics
- Data Warehouse: Definition and Characteristics
- ETL Process: Extract, Transform, Load
Unit 3: Business Data Analysis and Metrics
- Introduction to Business Data Analysis
- Descriptive Statistics: Mean, Median, Mode, Standard Deviation
- Trend Analysis
- Correlation Analysis
- Business Metrics and KPIs: Revenue growth rate, profit margin, customer acquisition cost (CAC), customer lifetime value (CLV), customer retention rate, churn rate, conversion rate, return on investment (ROI), sales growth, average order value (AOV), inventory turnover ratio, market share
- Role of Analytics in Business Decision Making
- Data-Driven Strategic Planning
Unit 4: Data Visualization and Power BI
- Introduction to Data Visualization and its Importance in Business Analytics
- Principles of Effective Data Visualization
- Charts and Graphs in Business Analytics (Conceptual Study): Bar Chart (concept, structure, advantages, and business applications), Line Chart (concept, use in trend analysis and time-series data), Pie Chart (concept, representing proportions and percentage distribution), Histogram (concept, representation of frequency distribution), Scatter Plot (concept, identifying relationships and correlation between variables)
- Selection of Appropriate Chart Types: When to use different charts, Comparison of chart types for business data
- Introduction to Microsoft Power BI
- Components of Power BI: Power BI Desktop, Power BI Service, Power BI Mobile
- Power BI Architecture
- Data Sources in Power BI
- Data Import and Data Transformation
- Creating Visualizations
- Dashboards and Reports
Unit 5: Applications of Business Analytics and AI
- Business Analytics in Decision Making
- Financial Analytics and Supply Chain Analytics
- Introduction to Artificial Intelligence in Business Analytics
- Role of AI in Business Decision Making
- AI Applications: Recommendation Systems, Customer Behaviour Analysis, Fraud Detection, Chatbots
- Ethical Issues in AI and Data Analytics
- Data Privacy and Security
About this course
Study materials, question papers, and solutions for Business Analytics (DI05000161) - Computer Engineering / Computer Science & Engineering, Semester 5