This document provides an introduction to business analytics. It defines business analytics as combining data, information technology, statistical analysis, quantitative methods, and computer-based models to provide decision makers with information and scenarios to make well-researched decisions. The document discusses the evolution of business analytics and its significance and uses, including making data-driven decisions and improving profitability. It also outlines some challenges of business analytics and describes the scopes of descriptive analysis, predictive analysis, and prescriptive analysis.
Basic Concepts of Business Data Analytics, Evolution of Business Analytics, Data Analytics, Business Data Analytics Applications, Scope of Business Analytics.
Basic Concepts of Business Data Analytics, Evolution of Business Analytics, Data Analytics, Business Data Analytics Applications, Scope of Business Analytics.
Data Analytics with R, Contents and Course materials, PPT contents. Developed by K K Singh, RGUKT Nuzvid.
Contents:
Introduction to Data, Information and Data Analytics,
Types of Variables,
Types of Analytics
Life cycle of data analytics.
This presentation is an Introduction to the importance of Data Analytics in Product Management. During this talk Etugo Nwokah, former Chief Product Officer for WellMatch, covered how to define Data Analytics why it should be a first class citizen in any software organization
Overview of Business Analytics and career lessons learnt / advice. Presentation delivered to Melbourne Business School - Masters of Business Analytics - July 2016.
I’m a young Pakistani Blogger, Academic Writer, Freelancer, Quaidian & MPhil Scholar, Quote Lover, Co-Founder at Essar Student Fund & Blueprism Academia, belonging from Mehdiabad, Skardu, Gilgit Baltistan, Pakistan.
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This presentation introduces big data and explains how to generate actionable insights using analytics techniques. The deck explains general steps involved in a typical analytics project and provides a brief overview of the most commonly used predictive analytics methods and their business applications.
Vijay Adamapure is a Data Science Enthusiast with extensive experience in the field of data mining, predictive modeling and machine learning. He has worked on numerous analytics projects ranging from healthcare, business analytics, renewable energy to IoT.
Vijay presented these slides during the Internet of Everything Meetup event 'Predictive Analytics - An Overview' that took place on Jan. 9, 2015 in Mumbai. To join the Meetup group, register here: http://bit.ly/1A7T0A1
Data Analytics with R, Contents and Course materials, PPT contents. Developed by K K Singh, RGUKT Nuzvid.
Contents:
Introduction to Data, Information and Data Analytics,
Types of Variables,
Types of Analytics
Life cycle of data analytics.
This presentation is an Introduction to the importance of Data Analytics in Product Management. During this talk Etugo Nwokah, former Chief Product Officer for WellMatch, covered how to define Data Analytics why it should be a first class citizen in any software organization
Overview of Business Analytics and career lessons learnt / advice. Presentation delivered to Melbourne Business School - Masters of Business Analytics - July 2016.
I’m a young Pakistani Blogger, Academic Writer, Freelancer, Quaidian & MPhil Scholar, Quote Lover, Co-Founder at Essar Student Fund & Blueprism Academia, belonging from Mehdiabad, Skardu, Gilgit Baltistan, Pakistan.
I am an academic writer & freelancer! I can work on Research Paper, Thesis Writing, Academic Research, Research Project, Proposals, Assignments, Business Plans, and Case study research.
Expertise:
Management Sciences, Business Management, Marketing, HRM, Banking, Business Marketing, Corporate Finance, International Business Management
For Order Online:
Whatsapp: +923452502478
Portfolio Link: https://blueprismacademia.wordpress.com/
Email: arguni.hasnain@gmail.com
Follow Me:
Linkedin: arguni_hasnain
Instagram : arguni.hasnain
Facebook: arguni.hasnain
This presentation introduces big data and explains how to generate actionable insights using analytics techniques. The deck explains general steps involved in a typical analytics project and provides a brief overview of the most commonly used predictive analytics methods and their business applications.
Vijay Adamapure is a Data Science Enthusiast with extensive experience in the field of data mining, predictive modeling and machine learning. He has worked on numerous analytics projects ranging from healthcare, business analytics, renewable energy to IoT.
Vijay presented these slides during the Internet of Everything Meetup event 'Predictive Analytics - An Overview' that took place on Jan. 9, 2015 in Mumbai. To join the Meetup group, register here: http://bit.ly/1A7T0A1
Data Analytics Certification in Pune-JanuaryDataMites
A data analytics course is an educational program designed to teach individuals the skills and techniques necessary for analyzing and interpreting data to extract meaningful insights.
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A data analytics course is an educational program designed to teach individuals the skills and techniques necessary for analyzing and interpreting data to extract meaningful insights.
For more details visit: https://datamites.com/data-analytics-certification-course-training-chennai/
Data analytics courses are educational programs designed to teach individuals the skills and techniques needed to work with data, analyze it, and extract meaningful insights.
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This presentation is about the requirements for completely exploiting data. Also,it deals with the actions needed for transforming the company's capabilities in big data models.
MIT School of Distance Education (MITSDE) offers a Post Graduate Certificate Program in Business Analytics course where you will gain expertise in the latest Business Analytics tools and techniques.
MITSDE’s PGCM Business Analytics course will equip you with concrete skills to apply at your workplace.
A sales quota is a quantitative goal assigned to a sales unit relating to a particular period of time.
A sales territory represents a group of customers or markets or geographical areas
“Sales promotion are those marketing activities that provide extra value or incentives to the sales force, the distributors, or the ultimate consumer and can stimulate immediate sales”.
“Sales promotion includes marketing devices for stimulating buyer interest and product trial.”
Transportation is the operational area of logistics that
geographically moves and positions inventory. Transportation system is the physical link connecting a company with the customers, raw material suppliers, plants, ware houses and
distribution channel members. The five basic transportation modes are Rail, Highway, Water, Pipeline.
Sales forecast is about estimating future sales.
Sales forecast is an estimated unit of sales in either rupees or number of units which could be sold for a specific period of time
Better sales forecasts
Enables a company to perform better
Make more informed decisions; and
Serves as a basis for determining the short run and the long term performance of a organization
Provide inputs for expected sales for a particular company or industry
Sales organization is a part of the total organization which is given the responsibility of selling of products manufactured by a company
It is another organization within the larger organization which is given the responsibility of selling function
It involves people working together for attaining the sales objectives of the company
It is concerned with planning, organizing, leading and controlling the activities of the sales force
Sales persons follow a sequence of activities while making a sale and these may be defined as different phases followed by salesperson.
A cycle start with prospect/potential customer identification, to converting him to a customer.
The sequential order of the steps may vary across selling situations
Objectives of sales management are derived from the organizations marketing objectives.
Ultimate sales objective of an organisation is to have a decent growth in sales.
More specifically, sales management objectives can be grouped under:
Quantitative Objectives (Short-term)
Qualitative Objectives (Long-term)
Sales and Sales Management: Meaning and DefinitionAmitabh Mishra
A sale is the pinnacle activity involved in selling products/services in return for money or other compensation. It is an act of completion of a commercial activity.
Sales is everything that you do to close the sale and get a signed agreement or contract.
Product Life Cycle shows the stages that products go through from development to withdrawal from the market.
The company’s differentiation and positioning strategies must change as the product, market, competitors changes over time.
Targeting, Differentiation and PositioningAmitabh Mishra
Once the firm has identified its market segment opportunity , it has to decide how many and which one to target.
•“Market targeting is a process of evaluating the market segments and identify one or more market segments to serve”.
Marketing Environment by Dr. Amitabh MishraAmitabh Mishra
•“Marketing Environment includes the actors and forces that affect management’s ability to build and maintain successful relationships with target customers”.
•These factors may be-
–Controllable: which the company can control
–Non-controllable: which the company can monitor and respond.
“Marketing Mix is set of marketing tools that the firm uses to pursue its marketing objectives in the target market”
"Marketing mix is a general phrase used to describe the different kinds of choices organizations have to make in the whole process of bringing a product or service to market”.
Companies approach and conduct business in different ways in order to achieve their organizational goals.
•Every company can have different ideas or philosophy. For example-
•A particular company can have its idea or philosophy that if the production is done on a large scale, the cost would be less and the product would be sold automatically.
Marketing is “The management process of anticipating, identifying and satisfying customer requirements profitably” (CIM, 2001).
•According to “The American Marketing Association” -“Marketing is the activity, set of institutions, and processes for creating, communicating, delivering, and exchanging offerings that have value for customers, clients, partners, and society at large” (AMA, 2007).
Dr
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It is a sample of an interview for a business english class for pre-intermediate and intermediate english students with emphasis on the speking ability.
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Business Valuation Principles for EntrepreneursBen Wann
This insightful presentation is designed to equip entrepreneurs with the essential knowledge and tools needed to accurately value their businesses. Understanding business valuation is crucial for making informed decisions, whether you're seeking investment, planning to sell, or simply want to gauge your company's worth.
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2. • Analytics is a field which combines 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.
Dr. Amitabh Mishra 2
3. 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.
Dr. Amitabh Mishra 3
4. – “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 analysing data to find out patterns that
will be helpful in developing strategies”
Dr. Amitabh Mishra 4
5. 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 operations research, which was extensively used during
World War II. 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.
Dr. Amitabh Mishra 5
6. • 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.
Dr. Amitabh Mishra 6
7. SIGNIFICANCE AND USAGES
OF BUSINESS ANALYITCS
• To make data-driven decisions
• Converts available data into valuable information.
• Eliminate guesswork
• Get faster answer to questions
• Get insight into customer behavior
• Get key business metrics reports when and where
needed
Dr. Amitabh Mishra 7
8. • 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 in competition
– Monitor KPIs (Key Performance Indicators) and
– React to changing trends in real time
Dr. Amitabh Mishra 8
9. CHALLANGES FOR BUSINESS ANALYITCS
• 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.
Dr. Amitabh Mishra 9
10. • 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 and
technology operations.
Dr. Amitabh Mishra 10
11. Scope of Business Analytics
• Business analytics has a wide range of
application and usages-
– Descriptive analysis
– Predictive analysis
– Prescriptive analysis
Dr. Amitabh Mishra 11
12. Descriptive Analysis
• This branch of Business Analytics analyses and finds
answer to the question-
“What has happened in the past?”.
• Descriptive analysis/ statistics performs the function
of “describing” or summarizing raw data to make it
easily understandable and interpretable by humans.
Dr. Amitabh Mishra 12
13. Predictive Analytics
• This branch of Business Analytics, uses forecasting
techniques and statistical models to find out-
What is going to happen in future?
• Predictive analysis helps us in predicting the future
course of events and taking necessary measures for the
same.
Dr. Amitabh Mishra 13
14. • Predictive analysis employ-
– Predictive modelling and Machine learning techniques.
• Predictive modeling uses statistics to predict outcomes.
• Machine learning(ML) statistical is the scientific
study of algorithms and models that computer systems use to
perform a specific task without using explicit instructions, relying
on patterns and inference instead. Machine learning algorithms
build a mathematical model based on sample data, known in order
to make predictions or decisions without being explicitly
programmed to perform the task.
Dr. Amitabh Mishra 14
15. Prescriptive Analytics
• This branch of Analytics, makes use of optimization and simulation
algorithms to find answer to the question-
“What should we do?”.
• Prescriptive Analysis is used to give advices on possible outcomes.
• This is a relatively new field of analytics that allows users to
recommend several different possible solutions to the problem and
to guide them about the best possible course of action.
Dr. Amitabh Mishra 15
16. USERS OF BUSINESS ANALYITCS
1. Students
2. Business man
3. Accountants and Auditors
4. Organization/Companies/Group of industries/
Small firm
Dr. Amitabh Mishra 16
17. MAIN SOFTWARE USED FOR BUSINESS
ANALYITCS
1. MS-EXCEL
2. SPSS
3. R
4. SAS
5. E-views
Dr. Amitabh Mishra 17
18. • 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.
Dr. Amitabh Mishra 18
19. MS-EXCEL in Business Analytics
– 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
Dr. Amitabh Mishra 19
21. Components of Business Analytics
• There are 6 major components/categories in
any analytics solution:
Dr. Amitabh Mishra 21
Components of
Business Analytics
Data Mining
Text Mining
Forecasting
Predictive Analytics
Optimization
Visualization
22. • 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
Dr. Amitabh Mishra 22
23. • 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
centre scripts etc. which are used to improve the
Product or Customer service or understand how
competitors are doing.
Dr. Amitabh Mishra 23
24. • 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
Dr. Amitabh Mishra 24
25. • Optimization– Use of simulations techniques to
identify scenarios which will produce best results.
E.g.
– Sale price optimization,
– Identifying optimal Inventory for maximum fulfilment
& avoid stock outs.
• Visualization– Enhanced exploratory data
analysis & output of modelling results with highly
interactive statistical graphics.
Dr. Amitabh Mishra 25