This document outlines a syllabus for a course on business analytics. It covers topics like introduction to analytics, statistics for business analytics, advanced Excel, R, data mining techniques like decision trees and clustering in R, time series forecasting, predictive modeling with logistic regression in R, and an overview of big data and Hadoop. It also defines key concepts like data analysis, data analytics, data mining. Descriptive, predictive, and prescriptive analytics techniques are discussed. Applications of business analytics in various domains like finance, marketing, HR, CRM, manufacturing, and credit cards are provided.

1. BUSINESS ANALYTICS
DR. YOGESH

2. SYLLABUS
Sr.
No.
Content Learning outcomes
Introduction to Analytics Basic understanding of business analytics
Statistics for Business Analytics Ability to apply various statistical tools and
techniques in the process of business analytics
Advanced Excel Proficiency Use of advanced Excel functions
Understanding R To understand use of R
Data Mining using Decision
Tree
Data mining techniques using R
Data Mining using clustering in
R
Data mining techniques using R
Time Series Forecasting Data mining techniques using R
Predictive Modelling – Logistic
Regression using R
Evaluation of models
Overview of Big Data and
Hadoop
Understand tools of business analytics
Data Analysis and Applications Ability to apply business analytic tools

3. DATA
DATA
ANALYSIS
DATA
ANALYTICS
DATA MINING

4. • ANALYSIS : DETAILED EXAMINATION OF THE ELEMENTS OR STRUCTURE OF SOMETHING,
TYPICALLY AS A BASIS FOR DISCUSSION OR INTERPRETATION
• ANALYTICS : THE SYSTEMATIC COMPUTATIONAL ANALYSIS OF DATA OR STATISTICS.

5. DATA ANALYTICS TOOL (COMPUTERSIED / PROGRAMS)
• MICROSOFT EXCEL
• SAS
• R
• PYTHON
• TABLEAU PUBLIC
• APACHE SPARK
• SPSS

6. STATISTICAL TOOL
• MEASURES OF LOCATION (MEAN/ MEDIAN/MODE/ GM)
• MEASURES OF VARIABILITY (RANGE/VARAINCE/SD)
• ANALYSING DISTRIBUTION (Z-SCORES)
• STATISTICAL COUNTING
• HYPOTHESIS TESTING
• SAMPLING METHOD
• REGRESSION
• PROBABILITY DISTRIBUTION

7. BUSINESS ANALYTICS
INFORMATION
DATA
WISDOMKNOWLEDGE

8. Techniques
of Analytics
Descriptive Predictive Prescriptive

9. DESCRIPTIVE ANALYTICS
• IT MAINLY REVOLVES AROUND GATHERING, ORGANIZING, TABULATING, PRESENTING
AND DEPICTING DATA AND DESCRIBING THE CHARACTERISTICS OF WHAT YOU ARE
STUDYING.
• IT IS MAINLY ABOUT WHAT IS HAPPENING.
• SO, WE HAVE TO TRY TO ANSWER THE QUESTION WHAT IS HAPPENING IN A
PARTICULAR CONTEXT LOOKING AT THE DATA.
• THIS IS ALSO FIRST PHASE OF ANALYTICS, THIS IS WHERE YOU ACTUALLY START, YOU
TRY TO GATHER THE SENSE OF WHAT IS HAPPENING AND THEN YOU LOOK FOR
OTHER THINGS OTHER CATEGORIES OF ANALYTICS.
• THEY DO NOT INFORM WHY THE RESULTS ARE HAPPENING OR WHAT CAN HAPPEN IN
FUTURE

10. PREDICTIVE ANALYTICS
• IT CAN BE USED TO PREDICT THE FUTURE.
• THE MAIN IDEA IS TO IDENTIFY ASSOCIATION AMONG DIFFERENT VARIABLES
AND PREDICT THE LIKELIHOOD OF A PHENOMENA OCCURRING ON THE BASIS OF
THOSE RELATIONSHIPS.
• WE NEED TO UNDERSTAND THE CONCEPT OF CORRELATION TO PREDICT
FUTURE.

11. PRESCRIPTIVE ANALYTICS
• PRESCRIPTIVE ANALYTICS IS ABOUT RECOMMENDING DECISIONS AND WHICH
ENTAILES GENERALLY IN MATHEMATICAL AND COMPUTATIONAL MODEL
• METHODS FROM DISCIPLINES LIKE STATISTICS, FORECASTING, DATA MINING,
EXPERIMENTAL DESIGN THEY ARE USED IN BUSINESS ANALYTICS
• LOTS OF SIMULATIONS TO FIND OUT WHAT CAN BE DONE ABOUT THIS FUTURE
SCENARIO OF THE BUSINESS OR RELEVANT TOPIC.

13. APPLICATIONS OF BUSINESS ANALYTICS
• FINANCE
BA IS OF UTMOST IMPORTANCE TO THE FINANCE SECTOR. DATA SCIENTISTS ARE IN
HIGH DEMAND IN INVESTMENT BANKING, PORTFOLIO MANAGEMENT, FINANCIAL
PLANNING, BUDGETING, FORECASTING, ETC
• MARKETING
STUDYING BUYING PATTERNS OF CONSUMER BEHAVIOUR, ANALYSING TRENDS, HELP IN
IDENTIFYING THE TARGET AUDIENCE, EMPLOYING ADVERTISING TECHNIQUES THAT
CAN APPEAL TO THE CONSUMERS, FORECAST SUPPLY REQUIREMENTS, ETC.
• HR PROFESSIONALS
HR PROFESSIONALS CAN MAKE USE OF DATA TO FIND INFORMATION ABOUT
EDUCATIONAL BACKGROUND OF HIGH PERFORMING CANDIDATES, EMPLOYEE
ATTRITION RATE, NUMBER OF YEARS OF SERVICE OF EMPLOYEES, AGE, GENDER, ETC.
THIS INFORMATION CAN PLAY A PIVOTAL ROLE IN THE SELECTION PROCEDURE OF A
CANDIDATE
• CRM
BA HELPS ONE ANALYSE THE KEY PERFORMANCE INDICATORS, WHICH FURTHER HELPS
IN DECISION MAKING AND MAKE STRATEGIES TO BOOST THE RELATIONSHIP WITH THE
CONSUMERS. THE DEMOGRAPHICS, AND DATA ABOUT OTHER SOCIO-ECONOMIC
FACTORS, PURCHASING PATTERNS, LIFESTYLE, ETC., ARE OF PRIME IMPORTANCE TO

14. • MANUFACTURING
BA CAN HELP YOU IN SUPPLY CHAIN MANAGEMENT, INVENTORY MANAGEMENT,
MEASURE PERFORMANCE OF TARGETS, RISK MITIGATION PLANS, IMPROVE EFFICIENCY
ON THE BASIS OF PRODUCT DATA, ETC.
• CREDIT CARD COMPANIES
CREDIT CARD TRANSACTIONS OF A CUSTOMER CAN DETERMINE MANY FACTORS:
FINANCIAL HEALTH, LIFE STYLE, PREFERENCES OF PURCHASES, BEHAVIORAL TRENDS,
ETC

15. Application
areas of
Business
Analytics
Policing/Security
Transportation
Fraud and
Risk
Detection
Delivery
Logistics
Manage
Risk
Proper
Spending City
Planning
Customer
Interactions
Internet/Web
Search
Healthcare
Digital Advertisement

16. SO, IN NUTSHELL IT HELPS IN;
• PRICING DECISIONS
• FINANCIAL AND MARKETING ACTIVITIES
• SUPPLY CHAIN MANAGEMENT
• MANAGEMENT OF CUSTOMER RELATIONSHIP
• HUMAN RESOURCE MANAGEMENT
• ENTERPRISE RESOURCE PLANNING

17. STUDY MATERIAL
• HTTPS://WWW.DIGITALVIDYA.COM/BLOG/DATA-ANALYTICS-APPLICATIONS/
• HTTPS://WWW.PROSCHOOLONLINE.COM/BLOG/APPLICATIONS-OF-BUSINESS-
ANALYTICS/