DM_course_detail.php Post ID = 23453 Business Analytics Courses in India | Business Analytics Training Program | Business Intelligence Courses in India - Edupristine.com
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Business Analytics

Classroom Prep

Business Analytics Classroom
We create 2.5 quintillion bytes of data everyday. So much that 90% of the data in the world today has been created in the last two years alone. Source: IBM Big Data

Big data has thus created opportunities like never before. Professionals who can analyze all this data & create useful information are highly sought after by companies across the world


About Business Analytics
• Business analytics focuses on developing new insights and understanding of business performance based on data and statistical methods.
• It makes extensive use of data, statistical and quantitative analysis, explanatory and predictive modeling and fact-based management to drive decision making.
• It focuses on Forecasting, Econometrics and Time Series Analysis and predicts future outcomes based on historical patterns.
Objective
Business Analytics is a specialized course designed to deliver knowledge on application of statistical concepts in real world scenarios. This course is designed to equip professionals working in Finance, Marketing, Economics, Statistical, Mathematics, Computer Science, IT, Analytics, Marketing Research, or Commodity markets with the essential tools, techniques and skills to answer important business questions.

Participants will be able to:
• Explore data to find new patterns and relationships (data mining)
• Predict the relationship between different variables (predictive modeling, predictive analytics)
• Predict the probability of default and create customer Scorecards (Logistic Regression)
After completion of this program, the participants:
• Understand a Problem in Business, Explore and Analyze the problem
• Solve business problems using analytics (in R) in different fields
Course Structure
Day 1: Introduction and Data Analytics
Introduction to Analytics - Overview • Analytics v/s Analysis
• Business Analytics
• Business domains within Analytics
Data - Topic covered • Summarizing Data
• Data Collection
• Data Dictionary
• Outlier Treatment
Case: Categorization of data variables Exploring credit card customer database to define the variable types and categorizing each type into relevant group.
Tool for Practice in Class MS Excel
Introduction to Commonly used Tools in Analytics R Software

Day 2: Multichannel Segmentation
Multichannel Segmentation – Topic Covered • Analytics v/s Analysis
• Business Analytics
• Business domains within Analytics
Data - Topic covered Identify differences in behavior of online, in-store & multi-channel shoppers
Identify the size of the opportunity for growth and begin to identify the methods to achieve it The value of the different shopper groups
Key measures to look at:
• Spend per visit
• Spend per shopper
• Units per visit
• Units per shopper
• Frequency of Purchase (Visits per shopper)
Case : Retail Analytics Case Synopsis : Understanding the value opportunity of focusing on the different shopper groups and framing analysis to better understand the multi-channel shoppers.
Domain Covered Finance Industry
Tool for Practice in Class R

Day 3 & 4: Linear Regression
Linear Regression – Topic Covered Correlation and Regression
Multivariate Linear Regression Theory
Coefficient of determination (R2) and Adjusted R2
Model Misspecifications
Economic meaning of a Regression Model
Bivariate Analysis
ANOVA (Analysis of Variance)
Multivariate Linear Regression Model
• Variable identification
• Response variable exploration
• Distribution analysis
• Outlier treatment
• Independent variables' analysis
• Heteroskedasticity detection and correction
• Multicollinearity detection and correction
• Fitting the regression
• Model performance check
Case: Multivariate Linear Regression Identify and Quantify the factors responsible for loss amount for an Auto Insurance Company
Domain Covered Insurance Industry
Tool for Practice in Class MS Excel and R

Day 5 & 6: Logistic Regression
Logistic Regression – Topics Covered Identifying problems in fitting linear regression on data having "Binary Response" variable
Introduction to Generalized Linear Modeling (GLMs)
Logistic Regression Theory
Logistic Regression Case
• Variable identification
• Response variable exploration
• Independent variables analyses
• Fitting the regression using SAS language
• Scoring equation
• Model diagnostics
• Analysis of results
• Check for reduction in Deviance/AIC
• Model performance check
• Actual vs Predicted comparison
• Lift/Gains chart and Gini coefficient
• K-S stat
• Score Card Development
Case: Multivariate Logistic Regression Identify bank customers who will most likely default in making the payment on balance due.
Domain Covered Banking Industry
Tool for Practice in Class MS Excel and R

Day 7: Decision Tree and Clustering
Decision Tree & Clustering – Topic Covered Data Mining and Decision Trees
Decision Tree Example
CHAID analysis
• Method and Algorithms
• Running the CHAID analysis and Interpreting the results
CART
• Running the CART analysis and Interpreting the results
When to use CART and when to use CHAID
Defining Clustering
Why and Where to use Clustering
Clustering methods
Clustering examples
K-means Clustering Algorithm
Case: CHAID & CART Analysis Identifying the classes of customer having higher default rate
Case: K-means Clustering Identifying similar groups in database containing auto insurance policy records using K-means Clustering
Domain Covered Insurance and Banking Industry
Tool for Practice in Class R

Day 8: Time Series Modeling
Logistic Regression – Topics Covered Models of time series
• Moving averages
• Autoregressive Models
The Box-Jenkins model building process
Model Estimation
Model Validation
Model forecasting
• Identify the ARIMA model
• Estimate the best ARIMA models
• Validate the model
• Forecast the sales based on model
Case : ARIMA Modeling Identify bank customers who will most likely default in making the payment on balance due.
Domain Covered Automobile Industry
Tool for Practice in Class R

Day 9: Logistic Regression
Logistic Regression – Topic Covered Identify and develop Dependent variable
Perform initial variable reduction and missing value imputation
Perform extreme value treatment
Prepare correlation matrix and VIF chart
Variable reduction through Multicollinearity
Perform Binning to prepare modeling dataset
Perform sampling to prepare training and validation dataset
Run the model
Develop report for model outcomes
Write the Scoring or implementation strategy
Case: Up-Sell Model Propensity Model for Up-Sell in Telecom Industry
Domain Covered Telecom Industry
Tool for Practice in Class R

Day 10: Market Basket Analysis
Association Rule – Topic Covered Affinity analysis to understand purchase behavior
Understanding Apriori algorithm
Capturing the insightful association available in the transaction records
Analysis of output results to plan store layout, promotions and recommendations
Case : Market Basket Analysis Understanding apriori algorithm to identify affinity among the purchase data in the basket based on historical transactions.
Domain Covered Retail Industry
Tool for Practice in Class R
Venue
City
Date
Address
Phone
(Toll Free)
Bangalore 23rd Aug Sanctum Technology Pvt Ltd, #114, Al-Azeem Center, Opp. Raheja Arcade, Above Food World, Koramangla, Banglore - 560095 18002005835
Chennai 23rd Aug Aec Business Academy, Kittu Complex, Giriappa Road, Near GRT Grand Hotel, T Nagar, Chennai 18002005835
Delhi 27th Sept 104, 1st Floor, Arunanchal Building Near Barakhamba Road Metro Gate No 4, Barakhamba Road, Connaught Place 18002005835
Hyderabad 30th Aug SRK Foundation, Plot No. 787, 2nd Floor, Apurupa Turbo Towers, Beside Croma Showroom, Road No. 36, Jubilee Hills, Hyderabad, Telangana 500033 18002005835
Kolkata 23rd Aug Mangalam Business Centre, 22, Camac Street. Block A, 6th Floor, Kolkata - 700016. Landmark: Pantaloons Building 18002005835
Mumbai 30th Aug 7th Floor, 702, Raaj Chambers, Old Nagardas Road, Near Andheri Subway, Andheri East 400069 18002005835
Pune 27th Sept Symbioisis Centre for Distance Learning 1065 B,Gokhale Cross Road, Model Colony Pune - 411016, Maharashtra, India 18002005835
Business Analytics
Price 30000
10 Days Classroom Training (50 Hours)
100 Hours Virtual Lab Practice (On SAS Language)
25 Hours Live - Instructor Based Training ( On SAS Language)
Pre-requisite Video Tutorial on Basic Statistic and Data, along with "R Studio" Software.
10 different domain case studies for practice purpose.
Subject wise Video recording for each module.
Webinar Video recording for each module.
Forum to Discuss with Fellow Students and Experts
Lecture Handout
Downloadable Course Material
Tool used for Training – Classroom Session - MS Excel ; R Studio and online :- SAS Language
24 * 7 Access to Online Materials
Certificate of Completion / Excellence
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Course Highlights
Extensive Classroom Training
10 Days Classroom Training (50 Hours)
100 Hours Virtual Lab Practice (On SAS Language)
Get hands-on experience on SAS language analytic Tool.
Discussion Forum
Access material any time. Write to us and get your doubts solved by our experts within 2 business days. You can also initiate a discussion by posting it on our active forum.
Online Materials
Download the whole material anytime during your 1 year subscription and use it for any future reference.
24x7 Online Access
24x7 Access to Course Material (Unlocked Excel Models, Presentations, etc.)
Certificate
A reference to get ahead in your career. At the end of the course, you will receive a Certificate of Participation. You can also earn the Certificate of Excellence upon completing our course assignment (Please get in touch with our sales representative for more details).
We sincerely appreciate the flexibility of teaching and customized guidance that the institute provided each of us. The intensity and rigour of the programme prepares one for high pressure situations. We are very grateful for the very valuable training and assistance provided to us by EDUPRISTINE.
I appreciate largely to the content part which covers practical aspects of modeling which we used on day to day base. We worked on R software expressively. We also touch on SPSS, Ms- Excel software. Edupristine done great job in combing the entire course..
FAQ
Who is the target audience? What are the prerequisites of this course? Where can I get doubt clarifications?
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