Business Analytics

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BUSINESS ANALYTICS ME03000151
FREE PDF ME03000151
Code: ME03000151 Credits: 3 Semester 3 IOT

Business Analytics

Get the full GTU study material, English & Gujarati textbook PDFs, syllabus curriculum, and solved previous year question papers.

Business Analytics Syllabus — Unit-wise Content

The official GTU curriculum for Business Analytics (subject code ME03000151) as prescribed for IOT · Semester 3 divides the course into 6 units, covering 50 listed topics. The unit-wise breakdown below is read from the GTU syllabus document for this subject code, so you can check what the course actually covers before deciding which papers to attempt.

Download the official syllabus PDF (ME03000151)

Unit 1 Unit-I

6 lecture hours

  • Business analytics: Overview of Business Analytics
  • Scope of Business analytics
  • Business Analytics Process
  • Relationship of Business Analytics Process and organization
  • competitive advantages of Business Analytics
  • Statistical Tools: Statistical Notation
  • Descriptive Statistical methods
  • Review of probability distribution and data modelling
  • sampling and estimation methods overview w. e. f
  • Academic Year: 2024-25 Semester: 3 Category of the Course: MOPEC Program Name: Master of Engineering Level: PG Subject Code: ME03000151 Subject Name: Business Analytics

Unit 2 Unit – II

6 lecture hours

  • Trendiness and Regression Analysis: Modelling Relationships and Trends in Data
  • simple Linear Regression
  • Important Resources
  • Business Analytics Personnel
  • Data and models for Business analytics
  • Visualizing and Exploring Data
  • Business Analytics Technology

Unit 3 Unit-III

8 lecture hours

  • Organization Structures of Business Analytics: Team management
  • Management Issues
  • Designing Information Policy
  • Ensuring Data Quality
  • Measuring the contribution of Business Analytics
  • Managing Changes
  • Descriptive Analytics
  • predictive analytics
  • predictive Modelling
  • Predictive analytics analysis
  • Data Mining
  • Data Mining Methodologies
  • Prescriptive analytics and its step in the business analytics Process
  • Prescriptive Modelling, and nonlinear Optimization

Unit 4 Unit-IV

12 lecture hours

  • Forecasting Models
  • Forecasting Models for Stationary Time Series
  • Forecasting Models for Time Series with a Linear Trend
  • Forecasting Time Series with Seasonality
  • Regression Forecasting with Casual Variables
  • Selecting Appropriate Forecasting Models
  • Monte Carlo Simulation and Risk Analysis: Monte Carle Simulation Using Analytic Solver Platform
  • New-Product Development Model
  • Newsvendor Model
  • Overbooking Model
  • Cash Budget Model

Unit 5 Unit-V

  • Decision Analysis: Formulating Decision Problems
  • Decision Strategies with the without Outcome Probabilities
  • Decision Trees
  • The Value of Information
  • Utility and Decision Making 8 20

Unit 6 Unit-VI

2 lecture hours

  • Recent Trends in : Embedded and collaborative business intelligence
  • Visual data recovery
  • Data Storytelling and Data journalism

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