Business Analytics with R

www.edureka.co/r-for-analytics
View Business Analytics with R Course at www.edureka.co/r-for-analytics
BUSINESS ANALYTICS WITH R

www.edureka.co/r-for-analytics
Objectives of this Session
 What is Business Analytics?
 Who uses R and How?
 What is R?
 Why to use R?
 R Products
 Job Trends in R
 Get started with R
 Use-case Implementation
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Source- http://www.mushroomnetworks.com/infographics/landscape-of-big-data
Landscape of Big Data

Business Analytics
Why Business Analytics is getting popular these days ?
Cost of storing data Cost of processing data

Cost of storing data ( 1980–2009)

Cost of processing Data ( 1992-2012)

Business Analytics
“Study of business data using statistical techniques and programming for creating decision support
and insights for achieving business goals”.
Business analytics is used to evaluate organization-wide operations, and can be implemented in any
department from sales to product development to customer service.
Business analytics solutions typically use statistical and quantitative analysis and fact-based data to
measure past performance to guide an organization's business planning.
Definition
Who creates it? How?
Who uses it? How?

Who uses R?

Who Uses R : Domains
 Telecom
 Pharmaceuticals
 Financial Services
 Life Sciences
 Education, etc

Who Uses R : Companies
Consumer Financial Protection Bureau
The Consumer Financial Protection Bureau uses R for data analysis
John Deere
Statisticians at John Deere use R for time series modeling and geospatial analysis in a
reliable and reproducible way. The results are integrated with Excel and SAP
Bank of America
Bank of America uses R for reporting
Foursquare
R is part of technology stack behind Foursquare’s famed recommendation engine

ANZ Bank
ANZ, the fourth largest bank in Australia, using R for credit risk analysis
Google
Google uses R to predict Economic Activity
Mozilla
Mozilla, the foundation responsible for the Firefox web browser, uses R to visualize Web
activity

Corporate Clients of R
http://www.revolutionanalytics.com/aboutus/our-customers.php

R : Characteristics
 R is open source and free.
 R has lots of packages and multiple ways of doing the same thing.
 By default stores memory in RAM.
 R has the most advanced graphics. You need much better programming skills.
 R has GUI to help make learning easier.
 Customization needs command line.
 R can connect to many database and data types.
“The great beauty of R is that you can modify it to do all sorts of things,” said Hal Varian, chief
economist at Google. “And you have a lot of pre-packaged stuff that’s already available, so
you’re standing on the shoulders of giants.”

What is R?

What is R : Data Analysis Software
 Data Scientists, Statisticians, Analysts,
Quants, and others who need to make
sense of data use R for statistical analysis,
data visualization, and predictive modelling.
 Rexer Analytics’s Annual Data Miner Survey
is the largest survey of data mining, data
science, and analytics professionals in the
industry.
 It has concluded that R's popularity has
increased substantially in recent years.
R is Data Analysis Software

What is R : Programming Language
 You do data analysis in R by writing scripts and
functions in the R programming language.
 R has also quickly found the following because
statisticians, engineers and scientists without
computer programming skills find it easy to use.
Do not get intimated by the
term ‘Programming Language’,
the concepts from the very
basic will be taught during the
course.
R is Programming Language

What is R : Environment for Statistical Analysis
 R language consists of functions for almost
every data manipulation, statistical model, or
chart that a data analyst could ever need.
 For statisticians, however, R is particularly
useful because it contains a number of built-
in mechanisms for organizing data, running
calculations on the information and creating
graphical representations of data sets.
R is Environment for Statistical Analysis

What is R : Open-source Software Project
 Not only does this mean that you can download
and use R for free, but the source code is also
open for inspection and modification to anyone
who wants to see how the methods and
algorithms work under the covers.
 R is an open-source program, and its popularity
reflects a shift in the type of software used
inside corporations.
R is Open-source Software Project

What is R : Community
 Additional functionality contributed to the R
language is by creating add-on "packages" for
use by the 2 million users of R worldwide. As a
result, there is a strong and vibrant community
of R users on-line.
 What makes R so useful — and helps explain its
quick acceptance — is that statisticians,
engineers and scientists can improve the
software’s code or write variations for specific
tasks.
R is Community

“R has really become the second
language for people coming out of
grad school now, and there’s an
amazing amount of code being
written for it,” said
Max Kuhn,
Associate Director of Nonclinical
Statistics at Pfizer.
Comparing R and others
“You can look on the SAS
message boards and see there
is a proportional downturn in
traffic.”
Comparing R : Job Trends
http://r4stats.com/articles/popularity/

Comparing R
Tool usage comparison
http://www.oreilly.com/data/free/files/stratasurvey.pdf

Comparing R
"R skills attract the highest salaries"
http://blog.revolutionanalytics.com/2014/02/r-salary-surveys.html

R Products
Companies Developing ‘R’ Products

Did you know Oracle creates a version of R?
http://www.oracle.com/technetwork/topics/bigdata/r-
offerings-1566363.html
R Products
Did you know SAS Institute views R as an
Opportunity?
http://support.sas.com/rnd/app/studio/Rinterface2.h
tml
Did you know Teradata uses R for in-
database analytics?
http://developer.teradata.com/applications/articles/in-
database-analytics-with-teradata-r
http://downloads.teradata.com/download/applications
/teradata-r

Basics Of R - Command Line
Basics of R - Command Line

Data Visualization in R
This plot represents the
locations of all the traffic
signals in the city.
It is recognizable as
Toronto without any other
geographic data being
plotted - the structure of
the city comes out in the
data alone.

Use Cases

Use-Cases
Problem statement : A retailer is interested to find out the association between the products. If retailers know that
which products are being bought together most of the time, then he can plan out the shelving of these products in
store or he can offer some discount on combo purchase.
We can run market basket analysis in R to find such kinds of pattern in data.
Use-Case #1

Use-Cases
Problem statement : Churn is the major problem for any telecommunication company. A telecom company wants to
find out the attributes of potential churn so that they can approach them with right retention offer.
For this we need to mine the historical data of previous churner & then we can run logistic regression to come up with a
churn probability equation.
Use-Case #2

Use-Cases
Problem statement : LAPD (Los Angles Police department) wants to predict the crime before it occurred.
They can use predictive modelling technique in R.
Use-Case #3

Use-Cases
Problem statement : Analyse the content of Obama's "Yes we can" speech. Mine this speech and find the most
frequently used words in the speech.
We can create a word cloud and represent the most frequently used words in the speech as bigger & bolder in the
Word Cloud.
Use-Case #4

Demo

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Business Analytics with R

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