ବାଣିଜ୍ୟ ଏନାଲେଟିକସ

Course Duration :    60 Hours

Course Fees  :    Rs. 10,520/-

Participant Profile:

• Thorough Understanding of Databases and Complex Queries from Database
• Clearing the “Database Bridge Course”

1. End Objective:
   • Appreciate need of Business Analytics in real life environment
2. Course Outline
   • Statistical Techniques
     • Different types of data
     • Frequency Distributions
     • Measures of central tendency and dispersion
     • Basic Probability
     • Normal Distribution
     • Central Limit Theorem
     • Hypothesis Testing
   • Regression
     • Simple and Multiple Linear Regression
     • R2 and Adj R2
     • ANOVA
     • Interpretation of coefficients
     • Dummy Variables
     • Residual Analysis
     • Outliers
     • Logistic Regression
     • Assumptions
     • Logistic Function
     • Chi-Square
     • 2 Log Likelihood
     • Classification Table
     • Interpreting Coefficients
     • Dependent Variable Prediction
   • Forecasting (Time Series)
     • Time Series vs. Causal Models
     • Moving Average
     • Exponential Smoothing
     • Trend, Seasonality
     • Cyclicity,
     • Causal modeling using linear regression
     • Forecast Accuracy

• Data Mining Techniques
  • Market Basket Analysis
  • Apriori
  • FPGrowth
  • Evaluation Methods: Lift, Kulc, IR, Chi –Square
  • Classification
  • Decision Tree Induction
  • Bayes Methods
  • Rule-Based Classification
  • Model Evaluation and Selection
  • Ensemble Approaches
  • Clustering
  • Partitioning Methods
  • Hierarchical Methods
  • Density-Based Methods
  • Grid-Based Methods
  • Evaluation of Clustering
• Excel Proficiency
  • Formatting of Excel Sheets
  • Use of Excel Formulae Function
  • Advanced Modeling Techniques
  • Data Filter and Sort
  • Charts and Graphs
  • Table formula and Scenario building
  • Lookups
  • pivot tables
• Introduction to R and SAS
  • Reading and writing data in R
  • Vectors, Frames and Subsets
  • Code Writing and R code Debugger
  • Managing and Manipulating Data in SAS
  • Creating Charts in SAS
  • Simple Linear Regression in SAS
  • Multiple Linear Regression in SAS
  • Data Mining in SAS
• Orientation of Big Data and Hadoop
  • Awareness of Big Data and Hadoop
  • Why is it relevant?
  • The four V’s,

• Is Big Data = Hadoop?
• Big Data and Cloud Computing
• Generators of Big Data
• Applications of Big Data
• Web Analytics and Mobile BI
  • Text Analytics
  • Sentiment Analytics
  • Click Analytics
  • Google Analytics
  • Difference between Web and Mobile Analytics
• Case Studies
  • Credit Risk Analytics
  • Financial Domain Case Study
  • Cross – Sell or Up –Sell
  • Marketing Domain Case Study

Customer Churn – HR Domain Case Study