Business Analytics

Business Analytics

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