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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



Upcoming Seminar

THE BUSINESS ANALYTICS BOOM

Business and the governments are finding ways to make sense of all the available data. Business Analytics thus finds favor as it is the use of tools and techniques like data mining, pattern matching, data visualizations and predictive modeling to predict and optimize outcomes and derive value from the data. Equipped with this useful information, organizations can compete better in cut-throat markets both locally and globally.

CREATE YOUR NICHE WITH OUR BUSINESS ANALYTICS PROGRAM

Today, data is everywhere. We create it simply with the touch of a button. But how much of it is actually useful? Whether you are in finance, operations, sales & marketing or planning, you maybe in touch with million data points everyday without being aware of how to derive valuable information from this data.

With EduPristine’s Business Analytics Program, you will be able to extract useful information from millions of bytes within minutes. This program focuses on Forecasting, Econometrics and Time Series Analysis and prediction of future outcomes based on historical patterns. It makes extensive use of data, statistical and quantitative analysis, explanatory and predictive modeling and fact-based management to drive decision making.

The program consists of classroom training with a specially designed 10 days hands-on workshop where you can start interpreting data along with projects and assignments that have a real-world case study mode rather than just theory. (It is compulsory to carry your personal laptop to the class)

BE A DATA WIZARD

The course will enable you 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)
  • Understand a Problem in Business, explore and analyze the problem
  • Use tools like R (open source) and Excel to interpret data
  • Solve business problems using analytics (in R) in different fields

THE IDEAL CANDIDATE FOR BUSINESS ANALYTICS

This course is designed to equip professionals working in the fields of Finance, Marketing, Economics, Statistics, Mathematics, Computer Science, IT, Analytics, Marketing Research, or Commodity markets with the essential tools, techniques and skills to answer important business questions.

There are no real skills you need to take this course, although basic mathematics and good analytical skills will be beneficial. However, the course is designed for people with minimal mathematical knowledge.

CAREER BENEFITS

The use of Business Analytics is widespread across all industries and functions, including Information Technology, Web/E-commerce, Healthcare, Law Enforcement, Banking and Insurance, Biotechnology, Human Resource Management. Some of the application areas include critical product analysis, target marketing, customer lifecycle management, customer service, social media behavior and link analysis, fraud detection, genetic research, inventory management, etc.

Below a list of a few Business Analytics roles across industries:
  • Data Analyst
  • Business Analyst
  • Financial Analyst
  • Marketing Analytics Manager
  • Pricing Analyst
  • Supply Chain Analyst
  • Website Analyst
  • Fraud Analyst
  • Retail Sales Analyst
  • Clinical Analyst

Course Structure

Tools for practice in class: MS Excel & R software

Day 1: Introduction and Data Analytics
Introduction to Analytics - Overview • Analytics v/s Analysis
Data - Topic covered • Summarizing Data
• Outlier Treatment
Case: Categorization of data variables Exploring credit card customer database to define variable types & categorizing them.

Day 2 & 3: Linear Regression
Linear Regression – Topic Covered Correlation and Regression
Multivariate Linear Regression Theory
Bivariate Analysis
ANOVA (Analysis of Variance)
Case: Multivariate Linear Regression Identify and Quantify the factors responsible for loss amount for an Auto Insurance Company
Domain Covered Insurance Industry

Day 4 & 5: Logistic Regression
Logistic Regression – Topics Covered Identifying problems in fitting linear regression on data having "Binary Response" variable
Generalized Linear Modeling (GLMs)
Logistic Regression Theory/Case
• Fitting the regression using SAS language
• Lift/Gains chart and Gini coefficient
• K-S stat
Case: Multivariate Logistic Regression Identify bank customers who will most likely default in making the payment on balance due.
Domain Covered Banking Industry

Day 6: Decision Tree and Clustering
Decision Tree & Clustering – Topic Covered Data Mining and Decision Trees
CHAID analysis
CART
Why and Where to use Clustering
Clustering methods
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

Day 7 & 8: Time Series Modeling
Logistic Regression – Topics Covered Models of time series
The Box-Jenkins model building process
• Identify the ARIMA model.
• Forecasting future sales based on historical data for an automobile company.
Case 1: Time Series Modeling using R
Case 2: ARIMA Modeling
Identify bank customers who will most likely default in making the payment on balance due.
Domain Covered Automobile Industry

Day 9: Logistic Regression
Logistic Regression – Topic Covered Identify and develop Dependent variable
Prepare correlation matrix and VIF chart
Variable reduction through Multicollinearity
Perform Binning to prepare modeling dataset
Run the model
Write the Scoring or implementation strategy
Case: Up-Sell Model Propensity Model for Up-Sell in Telecom Industry
Domain Covered Telecom Industry

Day 10: Market Basket Analysis
Association Rule – Topic Covered Affinity analysis to understand purchase behavior
Understanding Apriori algorithm
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

Course Highlights

ClassRoom Training
Get trained by topic experts with interactive learning in small batches.
25 Hrs Online Live Instructor base training (On SAS Language)
Learn Concepts once again though Live Online session on SAS language.
Lab Practical
100 Hrs - Virtual Lab practice (SAS Language)
65+ video Tutorials
Easy to follow byte sized video tutorials of over 1200 minutes created by topic experts. Learn the concepts at your own pace.
Study Notes
Download the study notes to supplement video tutorials.
Real-world Case Studies
Get the best training in analytics by understanding real world problems and scenarios
Analytical Tool - "R" Software
Get trained in R software to carry out Linear and Logistic Regression
Unlimited Download Access
Download the whole material anytime during your 1 year subscription and use it for any future reference.
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.

Venue

City
Date
Address
Phone
(Toll Free)
Bangalore 9th Nov Sanctum Technology Pvt Ltd, #114, Al-Azeem Center, Opp. Raheja Arcade, Above Food World, Koramangla, Banglore - 560095 18002005835
Chennai 11 Jan Aec Business Academy, Kittu Complex, Giriappa Road, Near GRT Grand Hotel, T Nagar, Chennai 18002005835
Delhi 16th Nov 104, 1st Floor, Arunanchal Building Near Barakhamba Road Metro Gate No 4, Barakhamba Road, Connaught Place 18002005835
Hyderabad 8th March SRK Foundation, Plot No. 787, 2nd Floor, Apurupa Turbo Towers, Beside Croma Showroom, Road No. 36, Jubilee Hills, Hyderabad, Telangana 500033 18002005835
Kolkata 4th Jan Camac Street, Kolkata 18002005835
Mumbai 16th Nov 7th Floor, 702, Raaj Chambers, Old Nagardas Road, Near Andheri Subway, Andheri East 400069 18002005835
Pune 9th Nov 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
Buy
FAQ
What's special about Edupristine program on Analytics? What is the eligibility for this program? Who should go for this course? What are the prerequisites of this course? Which Tools I will be learning? Is this classroom session? Is the program offered India wide? Is the course conceptual or hands-on? What are some of the job profiles at the entry level in Analytics? What kind of job description companies look forward? Which are the some of the big Analytics companies with operations in India? Why would one go for this field? What is the future scope in this domain? Can and should professionals with experience in some other fields switch to Analytics? Is this a theory oriented program or are will there also be practicals? Do I need to know programming to enroll into this program? I have no IT experience. Is this program for me? What kind of jobs am I likely to get after this training? Who will be teaching the programs?
Subjects like BA usually require a lot of time. Covering this topic during the session, which spans over 10 days, was a big task. Today I can say that I have good knowledge of all the key concepts and I can work my way through all the modules and I can go on to build my own modules now.
The course encourages me to explore this area further & it has been an interesting experience which helped us learn, shape out approach towards problems.
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