Docsity
Docsity

Prepare for your exams
Prepare for your exams

Study with the several resources on Docsity


Earn points to download
Earn points to download

Earn points by helping other students or get them with a premium plan


Guidelines and tips
Guidelines and tips

Business Analytics #2, Lecture notes of Business Administration

Lesson #2: > MEANING OF BUSINESS ANALYTICS > EVOLUTION OF BUSINESS ANALYTICS > SIGNIFICANCE AND USAGES OF BUSINESS ANALYTICS > CHALLENGES FOR BUSINESS ANALYTICS > USERS OF BUSINESS ANALYTICS > MAIN SOFTWARE USED FOR BUSINESS ANALYTICS > THE COMPONENTS OF BUSINESS ANALYTICS

Typology: Lecture notes

2024/2025

Available from 06/06/2025

ughlexisss
ughlexisss 🇵🇭

5 documents

1 / 2

Toggle sidebar

This page cannot be seen from the preview

Don't miss anything!

bg1
bUsIness AnaLYtICs
LEsson #2
ANALYTICS is a field which combined following into
one:
1. Data,
2. Information technology,
3. Statistical analysis,
4. Quantitative methods and
5. Computer-based models
This all are combined to provide decision makers all
the possible scenarios to make a well thought and
researched decision.
MEANING OF BUSINESS ANALYTICS
Business Analytics (BA) refers to
“The skills, technologies, practices for continuous
developing new insights and understanding of
business performance based on data and
statistical methods.”
“The practice of exploration of an organization’s
data with emphasis on statistical analysis.
Business analytics is used by companies
committed to data-driven decision making.
“The statistical analysis of the data a business has
acquired in order to make decisions that are based
on evidence rather than a guess.”
“A combination of data analytics, business
intelligence and computer programming. It is the
science of analyzing data to find out patterns that
will be helpful in developing strategies.
EVOLUTION OF BUSINESS ANALYTICS
Business analytics has been existence since very
long time and has evolved with availability of
newer and better technologies.
It has its roots in operation research, which was
extensively used during World War ll. Operations
research was an analytical way to look at data to
conduct military operations.
Over a period of time, this technique started
getting utilized for business. Here operations
research evolved into management science. Again,
basis for management science remained same as
operation research in data, decision making
models, etc.
As the economies started developing and
companies became more and more competitive,
management science evolved into:
Business intelligence,
Decision support systems and into
PC software.
SIGNIFICANCE AND USAGES OF BUSINESS ANALYTICS
To make data-driven decisions
Converts available data into valuable information
Eliminate guesswork
Get faster answer to questions
Get insights into customer behavior
Get key business metrics reports when and where
needed.
It impacts functioning of the whole organization.
And hence, can:
Improve profitability of the business
Increase market share and revenue and
Provide better return to a shareholder
Reduce overall cost
Sustain competition
Monitor KPIs (Key Performance Indicators)
and
React to changing trends in real time
CHALLENGES FOR BUSINESS ANALYTICS
Business analytics depends on sufficient
volumes of high-quality data.
The difficulty in ensuring data quality.
Data warehousing require a lot more storage
space than it did speed.
Business analytics is becoming a tool that can
influence the outcome of customer interactions.
Technology infrastructure and tools must be
able to handle the data and Business Analytics
processes.
Organizations should be prepared for the
changes that Business Analytics bring to
current business technology operations.
USERS OF BUSINESS ANALYTICS
1. Students
2. Business man
3. Accountants and Auditors
4. Organization / Companies / Group of
Industries / Small Firm
MAIN SOFTWARE USED FOR BUSINESS ANALYTICS
1. MS-EXCEL
2. SPSS
3. R
4. SAS
5. E-VIEWS
pf2

Partial preview of the text

Download Business Analytics #2 and more Lecture notes Business Administration in PDF only on Docsity!

bUsIness AnaLYtICs

LEsson # 2

ANALYTICS is a field which combined following into one:

  1. Data,
  2. Information technology,
  3. Statistical analysis,
  4. Quantitative methods and
  5. Computer-based models This all are combined to provide decision makers all the possible scenarios to make a well thought and researched decision. MEANING OF BUSINESS ANALYTICS Business Analytics (BA) refers to ➢ “The skills, technologies, practices for continuous developing new insights and understanding of business performance based on data and statistical methods.” ➢ “The practice of exploration of an organization’s data with emphasis on statistical analysis. Business analytics is used by companies committed to data-driven decision making. ➢ “The statistical analysis of the data a business has acquired in order to make decisions that are based on evidence rather than a guess.” ➢ “A combination of data analytics, business intelligence and computer programming. It is the science of analyzing data to find out patterns that will be helpful in developing strategies.” EVOLUTION OF BUSINESS ANALYTICS ➢ Business analytics has been existence since very long time and has evolved with availability of newer and better technologies. ➢ It has its roots in operation research, which was extensively used during World War ll. Operations research was an analytical way to look at data to conduct military operations. ➢ Over a period of time, this technique started getting utilized for business. Here operation’s research evolved into management science. Again, basis for management science remained same as operation research in data, decision making models, etc. ➢ As the economies started developing and companies became more and more competitive, management science evolved into:  Business intelligence,  Decision support systems and into  PC software. SIGNIFICANCE AND USAGES OF BUSINESS ANALYTICS  To make data-driven decisions  Converts available data into valuable information  Eliminate guesswork  Get faster answer to questions  Get insights into customer behavior  Get key business metrics reports when and where needed.  It impacts functioning of the whole organization. And hence, can: ➢ Improve profitability of the business ➢ Increase market share and revenue and ➢ Provide better return to a shareholder ➢ Reduce overall cost ➢ Sustain competition ➢ Monitor KPIs (Key Performance Indicators) and ➢ React to changing trends in real time CHALLENGES FOR BUSINESS ANALYTICS
  • Business analytics depends on sufficient volumes of high-quality data.
  • The difficulty in ensuring data quality.
  • Data warehousing require a lot more storage space than it did speed.
  • Business analytics is becoming a tool that can influence the outcome of customer interactions.
  • Technology infrastructure and tools must be able to handle the data and Business Analytics processes.
  • Organizations should be prepared for the changes that Business Analytics bring to current business technology operations. USERS OF BUSINESS ANALYTICS
  1. Students
  2. Business man
  3. Accountants and Auditors
  4. Organization / Companies / Group of Industries / Small Firm MAIN SOFTWARE USED FOR BUSINESS ANALYTICS
  5. MS-EXCEL
  6. SPSS
  7. R
  8. SAS
  9. E-VIEWS

SPSS – SPSS Statistics is a software package used for statistical analysis. Long produced by SPSS Inc., it was acquired by IBM in 2009. The current versions (2014) are officially named IBM SPSS Statistics. MS-EXCEL – Microsoft Excel is a spreadsheet application developed by Microsoft for Microsoft Windows. It features calculation, graphing tools, pivot tables, and a macro programming language called Visual Basic for Applications. THE BUSINESS ANALYTICS PROCESS THE COMPONENTS OF BUSINESS ANALYTICS There are 6 major components/categories in any analytics solution: DATA MINING – Create models by uncovering previously unknown trends and pattern in vast amounts of data e.g. detect insurance claims frauds, Retail Market basket analysis. There are various statistical techniques through which data mining is achieved. ➢ Classification (when we know on which variables to classify the data e.g. age, demographics) ➢ Regression ➢ Clustering (when we don’t know on which factors to classify data) ➢ Associations & Sequencing Models TEXT MINING – Discover and extract meaningful patterns and relationships from text collections. E.g. ➢ Understand sentiments of customers on social media sites like Twitter, Face Book, Blogs, Call Center Scripts, etc., which are used to improve the Product of Customer service or understand how competitors are doing. FORECASTING – Analyze & forecast processes that take place over the period of time. E.g. ➢ Predict seasonal energy demand using historical trends, ➢ Predict how many ice creams cones are required considering demand. PREDICTIVE ANALYTICS – Create, manage and deploy predictive scoring models. E.g. ➢ Customer churn & retention, ➢ Credit scoring, ➢ Predicting failure in shop floor machinery OPTIMIZATION – Use of simulations techniques to identify scenarios which will produce best results. E.g. ➢ Sale price optimization, ➢ Identifying optimal inventory for maximum fulfillment & avoid stock outs. VISUALIZATION – Enhanced exploratory data analysis and output modelling results with highly interactive statistical graphics.