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© EduPristine For [Business Analytics]© EduPristine – www.edupristine.com
Business AnalyticsCourse Catalogue
ABHAY MAHALLEY
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Business Analytics Program
© EduPristine For [Business Analytics]
What is Analytics:-
Analytics is the application of computer technology, statistics and domain knowledge to solveproblems in business and industry, to aid efficient and effective design making.
Analytics is the simply the scientific process of converting row data into knowledge to supportdesign making.
Analytics involves finding patterns in data.
The goal of Analytics is to improve business, society or personal performance by gainingknowledge from data.
Analytics is moving design making from Gut feel and guesstimates to better, more informed onesdriven by data.
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About Data:-
Data is growing at 40% compound annual rate reaching by 45ZB by 2020
2.5 Quintillion bytes of data created each yr.
90% of data in world was created in last 2 yr.
Why is Analytics is USED-
Design making is now fact and performance based.
Intuition is out, metrics are in.
Shorter time to market, demanding customer.
Make each and every dollar count and increase return on investment.
The real time design.
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Different types of Analytics:-
What happened or happening in the business?-Descriptive Analytics
Why did it happened?-Inquisitive Analytics
What is likely to happen based on historical Information?-Predictive Analytics
What action should be taken?-Prescriptive Analytics
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Business Analytics-Concepts
Statistical Analysis-Why is this happening?
Forecasting-what if these trends continues?
Predictive modelling-what will happen next?
Optimization –What’s the best that can happen?
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Business Analysis Vs Business Analytics
Business Analysis-
Creating business Architecture.
Requirement Elicitation, Documentation of Requirements.
Business Process Analysis.
Business Analytics-
Mine a data ware house to report past performance.
Analyze why something happened.
Create predictive models to understand what would happen in a given scenario.
Prescribe a strategy based on rigorous statistical analysis of data to ensure results.
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Why is Analytics used?
Decision making is now fact and performance based
Intuition is out, metrics are in
Intense connotation, shorter time –to –market, demanding customers
Make each and every dollar count and increase return on investment
The real- time decisions
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Uses of Analytics
Marketing
Customer Segmentation
Up Selling/Cross Selling
Market Basket Analytics
Marketing Media Mix Analysis
Financial Sector
Credit Risk Management
Credit Scorecard Modeling
Fraud Detection
Stock Market Analysis
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Uses of Analytics
Retail Analytics
Shelf space allocation
Analysis of customers preference for store brand or brand names
Pricing decisions
Promotions and product bundle offerings
Media Analytics
Decision making on allocation of air- time of a new TV show
Prime time rate for advertisement
Analysis of channel viewership
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What The Market Buzz On Analytics
India’s analytics market to double to us$ 2.3 bn by 2018-Nasscom
Analytics outsourcing to grow from us$ 42bn to us$ 71bn in 2016-Nasscom
83% business leaders globally identified as their top priority-IBM
Shortage of 1.5mn business analytics professional by 2018-McKinsey
India has become a global analytic hub-Times of India
The next big job boom is in analytics-up to 250k job openings in analytics over next 2 yrs. starting salaries to be in region od Rs 5-9lacs PA-DNA
Indian companies grooming data scientists to feed global jobs demand-Business Today
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Training Objective-EduPristine
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, Economist,
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 Studio”) in different fields
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Pre-requisites:-
Pre-requisites for the course:
The participants are expected to have the basic understanding of the following topic:
* Basic Statistics
EduPristine provides comprehensive recordings of basis statistics concept along with its Business Analytics course ware.
*Should have good analytical skills.
*Basic Excel knowledge.
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Day 1 & 2 :(Online)-Basic StatsDay 3 :Introduction and Data Analytics
Day 3 :Introduction and Data Analytics
Introduction to Analytics - Overview Analytics v/s AnalysisBusiness AnalyticsBusiness 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 MS Excel
Introduction to Commonly used Tool in Analytics R software
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Day 4 & 5 : Linear Regression
Day 4 & 5 : Linear Regression
Linear Regression – Topic Covered
Correlation and RegressionMultivariate Linear Regression TheoryCoefficient of determination (R2) and Adjusted R2Model MisspecificationsEconomic meaning of a Regression ModelBivariate AnalysisANOVA (Analysis of Variance)Multivariate Linear Regression Model Variable identification Response variable exploration
Distribution analysis Outlier treatment
Independent variables analyses 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 MS Excel and R
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Day 6 & 7 : Logistic Regression
Day 6 & 7 : Logistic Regression
Logistic Regression – Topic Covered
Identifying problems in fitting linear regression on data having “Binary Response” variableIntroduction to Generalized Linear Modeling (GLMs) Logistic Regression TheoryLogistic 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 Linear 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 R
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Day 8: Decision Tree and Clustering
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Day 8: Decision Tree and Clustering
Decision Tree & Clustering – Topic Covered
Data Mining and Decision TreesDecision Tree ExampleCHAID analysisMethod and AlgorithmsRunning the CHAID analysis and Interpreting the resultsCARTMethod and AlgorithmsRunning the CART analysis and Interpreting the resultsWhen to use CART and when to use CHAIDDefining ClusteringWhy and Where to use ClusteringClustering methodsClustering examplesK-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
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Day 9 & 10 : Time Series Modeling
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Day 9 & 10 : Time Series Modeling
Time Series Modeling – Topic Covered
Models of time series Moving averages Autoregressive ModelsThe Box-Jenkins model building processModel EstimationModel ValidationModel forecasting Identify the ARIMA model Estimate the best ARIMA models Validate the model Forecast the sales based on model
Case I: Time Series Modeling on RCase II: ARIMA Modeling
Forecasting future sales based on historical data for an automobile company.
Domain Covered Automobile Industry
Tool for Practice in Class R
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Day 11: Logistic Regression
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Day 11 : Logistic Regression
Logistic Regression – Topic Covered
Identify and develop Dependent variablePerform initial variable reduction and missing value imputationPerform extreme value treatmentPrepare correlation matrix and VIF chartVariable reduction through MulticollinearityPerform Binning to prepare modeling datasetPerform sampling to prepare training and validation datasetRun the modelDevelop report for model outcomesWrite 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
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Day 12: Market Basket Analysis
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Day 12 : Market Basket Analysis
Association Rule – Topic Covered
Affinity analysis to understand purchase behaviorUnderstanding Apriority algorithmCapturing the insightful association available in the transactionrecordsAnalysis of output results to plan store layout, promotions andrecommendations
Case : Market Basket AnalysisUnderstanding apriority algorithm to identify affinity among thepurchase data in the basket based on historical transactions.
Domain Covered Retail Industry
Tool for Practice in Class R
Session End
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Case studies (20Hrs Classroom Session)-Optional
Case Synopsis
Cross Sell Model Propensity to Cross sell health insurance products to general insurance customers.
Market Mix Modeling Optimization of the promotion expense using Market mix modeling
Churn Analytics Developing a churn model to gauge the propensity of attrition among loyal and profitable customer segment.
Buy Till You Die Model Predicting the future number of transactions a customer will make, thereby calculating the value of the customer in his/her lifetime.
Customer Lifetime Value Analysis Predicting the customer survival along with the profitability to model the life time value of each customer
Telecom Model to Estimate Bill Building a model that can suggest right tariff plan based on estimated bill amount
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Data Visualization (20Hrs Classroom Session)-Optional
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Data Visualization (20Hrs Classroom Session)-Optional
Introduction
The visualization design methodology
The Data Visualization Process
Working with Single Data Sources
Using Multiple Data Source
Using Calculations in Tableau
Comparing Measures Against a Goal
Tableau Geo coding, Advanced Mapping
Showing Distributions of Data
Statistics and Forecasting
Dashboard Best Practices
Sharing Your Work
Case Study
Exam/Exam Preparation
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Course Features BA
Training Highlight
10 Days Classroom Training (50 Hours) :- Get trained by topic experts with interactive learning.
100 Hours Virtual Lab Practice (On SAS Language) :- Get hand on experience on SAS language analytic Tool.
25 Hours Live - Instructor Based Training ( On SAS Language) :- Get trained on SAS Language through Live Instructor.
Pre-requisite Video Tutorial on Basic Statistic and Data, along with "R Studio" Software :- Prepare yourself before attending the classes by referring Basic Stats videos.
Different domain case studies for practice purpose. Get the best training in analytics by understanding real world problems and scenarios
Subject wise Video recording for each module. Download the study notes to supplement video tutorials.
Webinar Video recording for each module. Download the recording to understand the topic in better way.
Forum to Discuss with Fellow Students and Experts 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.
Lecture Handout Refer lecture material before & after the session
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Course Features BA
Training Highlight
Downloadable Course Material Download the whole material anytime during your 1 year subscription and use it for any future reference.
Tool used for Training – Classroom Session - MS Excel ; R Studio and online :- SAS Language Get hand on experience of various analytic tools.
24 * 7 Access to Online Materials 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.
Certificate of Completion / Excellence 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).
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BA-Plus And Premium-Optional
Case Studies:-
Get additional 4 Days Domain/Industry Specific Training.
Data Visualization Program Features:-
• 20 Hrs. Classroom Training
– Get trained by topic experts with interactive learning in small batches.
• Exam Preparation Session
– Prepare rigorously before competitive exam.
• Assignments & cases
– Work on real time cases from different domains.
• 24x7 Online Access
– to Course Material (Unlocked Excel Models, Presentations, etc.)
• Doubt Solving By Experts
– 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 active forums.
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Course Highlights
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Course Highlights BA PRO BA PLUS BA PREMIUMRs. 30,000 Rs. 45,000 Rs. 60,000
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
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
4 Days Industrial Case Studies For Practice purpose -(20 Hours)
4 Days Data Visualization Training -(20 Hours)
PPT for Data Visualization Preparation
Data Visualization Assignments for practice
Exam Preparation SessionPreparing for Data visualization global Certification
Tableau Desktop version 8. examination:Exam Registration-$250 Fees Included
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Available Packages
Packages Available
BA-Pro BA-Plus BA- Premium
Rs.30,000 Rs.45,000 Rs.60,000
BA TrainingBA Training + Case Studies
+ Data Visualization training
BA Training + Case Studies + Data Visualization training + Tableau
certification
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Payment Mode
Procedure to ENROLL
Online Payment via Net Banking transfer or by log on to www.edupristine.com
• <click<Fees<Buy (debit/credit card)
The bank details are given below:
• Bank Account Name: Neev Knowledge management Pvt. Ltd
• Bank Name: HDFC
• Branch Address: Maneji Wadia building, ground floor, Nanik Motwani Marg fort, Mumbai,
• Account Number: 00602560008449
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• Account Type: Current
• Address: 702, Raaj Chambers, Near Andheri Subway, Old Nagardas Road, Andheri East Mumbai 69
Cash Payment (Handover to venue co-ordinator & collect the receipt on spot)
Cheque Payment in favor of “Neev Knowledge Management Pvt Ltd”
For Registration Please Contact: Anjana Singh-022 40938527 / 08879342887
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support@edupristine.com
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See you in Class…Anjana Singh
anjana@edupristine.com
+91- 22 4093 8527/088 793 42 887