JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY HYDERABAD

17MBA17: DATA ANALYTICS

MBA III Semester (R17)

Overview

Learning Objective: To understand the importance of ever-increasing volume, variety and velocity of data in organization and application of data analytical tools for decision making.

Learning Outcome

Students will be able to understand a) Importance of Analytics b) Understanding

the analytical tools c) Application of Analytical tools to solve business problems.

UNIT - I

Introduction to Data Analytics: Introduction to Data- Importance of Analytics- Data for Business Analytics –Big Data - Business Analytics in Practice. Data Visualization – Data Visualization tools, Data queries, Statistical methods for Summarizing data, Exploring data using pivot tables.

UNIT - II

Descriptive Statistical Measures – Population and samples, Measures of location, Measures of Dispersion, Measures of variability, measures of Association. Probability distribution and Data Modeling – Discrete Probability distribution, Continuous Probability distribution, Random sampling from Probability Distribution, Data Modeling and Distribution fitting.

UNIT - III

Predictive Analytics: Karl Pearson Correlation Techniques - Multiple Correlation-Spearman’s Rank correlation-Simple and Multiple regression-Regression by the method of least squares – Building good regression models – Regression with categorical independent variables - - Linear Discriminant Analysis-One way and Two Way ANOVA

UNIT - IV

Data Mining : Scope of Data Mining, Data Exploration and Reduction, Unsupervised learning – cluster analysis, Association rules, Supervised learning- Partition Data, Classification Accuracy, prediction Accuracy, k-nearest neighbors, Classification and regression trees, Logistics Regression.

UNIT - V

Simulation: Random Number Generation, Monte Carlo Simulation, What if Analysis, Verification and Validation, Advantages and Disadvantages of Simulation, Risk Analysis, Decision Tree Analysis.