Business analytics !!

© EduPristine For [Business Analytics]© EduPristine – www.edupristine.com

Business AnalyticsCourse Catalogue

ABHAY MAHALLEY

© EduPristine For [Business Analytics] 1

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



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



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



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


Session End


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


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


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)

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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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© EduPristine For [Business Analytics]© EduPristine – www.edupristine.com

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See you in Class…Anjana Singh

[email protected]

+91- 22 4093 8527/088 793 42 887