Decision making in the era of cloud computing and big data

AN INTRODUCTION TO BIG DATA ANALYTICS AND CLOUD COMPUTING
a talk on Decision Making in
Big Data and Cloud Computing era
May 10, 2014 (1400-1600 Hrs)
in
Room no. 511, Fifth floor,
Department of Management Studies,
Vishwakarma Bhawan, IIT Delhi

Your speaker
Ajay Ohri
R for Business Analytics http://www.springer.com/statistics/book/978-1-4614-4342-1

My requirements
What are the key challenges to Data Analytics? How to capture unstructured data and then process it, so that it can
be used for analysis? Which methodology can be more efficient to handle Big Data ? What are the key technologies that can help to
process Big Data?
What skill sets are required to become a Data Scientist? What are the possible key areas for research in Big Data Analytics? What level of
programming skills is required to work in this area? Which packages/algorithms are useful ? Does R support some inbuilt functionality to make
efficient use of multi-core processors ?
How R can be used to do data mining in Social Network Data? Can it help HR persons to do analytics to hire right set of people (HR
Analytics) ?
How R can be used to perform Regression, Classification, Clustering, Structural Equation Modeling and Data Envelopment Analysis? Illustrate
with real life example.
How Cloud computing can help in processing or analyzing data efficiently? What are the risks associated with using Cloud-based
model?

My requirements- let’s break this down
be used for analysis? Which methodology can be more efficient to handle Big Data ? What are the key technologies that can help to
process Big Data?
programming skills is required to work in this area? Which packages/algorithms are useful ? Does R support some inbuilt functionality to make
efficient use of multi-core processors ?
How R can be used to do data mining in Social Network Data? Can it help HR persons to do analytics to hire right set of people (HR
Analytics) ?
with real life example.
model?

My requirements- let’s sort this up
be used for analysis?
model?
Which methodology can be more efficient to handle Big Data ? What are the key technologies that can help to
process Big Data?
programming skills is required to work in this area? Can it help HR persons to do analytics to hire right set of people (HR
Analytics) ?
How R can be used to do data mining in Social Network Data?
with real life example. Which packages/algorithms are useful ? Does R support some inbuilt functionality to make efficient use of multi-core
processors ?

My requirements- let’s tag this down
model?
process Big Data?
Analytics) ?
processors ?
Data Analytics and Cloud Computing
Big Data
R
R (Data Science Careers)

My requirements- let’s check this again
model?
process Big Data?
Analytics) ?
processors ?
Data Analytics and Cloud Computing
Big Data
R
R (Data Science Careers)
Incorrect Classification?

Topics to be covered
Business Analytics
Data Science
Big Data
Cloud Computing
R

Sub- topics to be covered
Business Analytics -methodologies, challenges,structured /unstructured data
Data Science
Big Data
Cloud Computing
R

Business Analytics -methodologies, challenges,structured /unstructured data,HR analytics
Data Science -careers, skills
Big Data - Technology, skills
Cloud Computing
R

Cloud Computing -technology,risks
R-

Cloud Computing -technology,risks
R- ???

Sub- topics that won’t be covered
R- Data Envelopment Analysis (http://professorjf.webs.com/DEA%202013.pdf )
http://www.uri.edu/artsci/ecn/burkett/DEAnotes.pdf
Structural Equation Modeling ( http://socserv.socsci.mcmaster.ca/jfox/Misc/sem/SEM-paper.pdf )
http://cran.r-project.org/doc/contrib/Fox-Companion/appendix-sems.pdf
and if time permits
HR Analytics
http://www.slideshare.net/ajayohri/hr-analytics-34080636

Business Analytics
Definition
Business analytics (BA) refers to the field of
exploration and investigation of data generated by businesses.
Business Intelligence (BI) is the seamless dissemination of
information through the organization, which primarily involves business metrics both past and current for the use of
decision support in businesses.
Data Mining (DM) is the process of discovering
new patterns from large data using algorithms and statistical methods.
To differentiate between the three, BI is mostly current reports, BA is models to predict and strategize and DM matches patterns in
big data.

Business Analytics
Definition
-Information Ladder
-CRISP DM
-KDD
-SEMMA

Business Analytics
-Information Ladder
Data → Information → Knowledge → Understanding → Insight → Wisdom
Whereas the first two steps can be scientifically exactly defined, the upper parts belong to the domain of psychology and
philosophy.
Also DIKW

Data Mining - a good map http://www.saedsayad.com/

Data Science
https://s3.amazonaws.com/aws.drewconway.com/viz/venn_diagram/data_science.html

What is a Data Scientist
a data scientist is simply a person who can
write code
understand statistics
derive insights from data

Oh really, is this a Data Scientist ?
a data scientist is simply a person who can
write code = in R,Python,Java, SQL, Hadoop (Pig,HQL,MR) etc
= for data storage, querying, summarization, visualization
= how efficiently, and in time (fast results?)
= where on databases, on cloud, servers
and understand enough statistics
to derive insights from data
so business can make decisions

Some tools
Linux
+
Java /Python/Pig
+
R
+
SQL

Cheat Sheets for Data Scientists
http://www.slideshare.net/ajayohri/cheat-sheets-for-data-scientists

Data Scientist Programming Skills
Java http://www.learnjavaonline.org/
Python http://www.codecademy.com/tracks/python
SQL http://www.w3schools.com/sql/
R http://bigdatauniversity.com/bdu-wp/bdu-course/introduction-to-data-analysis-using-r/
http://www.statmethods.net/
Hadoop http://hortonworks.com/hadoop-training/
Linuxhttps://github.com/WilliamHackmore/linuxgems/blob/master/cheat_sheet.org.sh

Other place to learn
MOOCs 1 https://www.edx.org/ 2 https://www.coursera.org/ 3 https://www.udacity.com/ 4 https://www.udemy.com/
Books
Courses
Workshops

Statistics on Facebook
https://newsroom.fb.com/company-info/
● 802 million daily active users on average in March 2014
● 609 million mobile daily active users on average in March 2014
● 1.28 billion monthly active users as of March 31, 2014
● 1.01 billion mobile monthly active users as of March 31, 2014

Statistics on Twitter
https://about.twitter.com/company
● 255 million monthly active users
● 500 million Tweets are sent per day
● 78% of Twitter active users are on mobile
● 77% of accounts are outside the U.S.

Big Data
is changing marketing
is changing marketing models
is much more quantitative compared to earlier
marketing

Hadoop - infrastructure for Big Data
http://hadoop.apache.org/

Cloud Computing -HW to the SW
http://csrc.nist.gov/publications/nistpubs/800-145/SP800-145.pdf
http://www.silverlighthack.com/post/2011/02/27/iaas-paas-and-saas-terms-explained-and-defined.aspx

Cloud Computing
http://www.silverlighthack.com/post/2011/02/27/iaas-paas-and-saas-terms-explained-and-defined.aspx

Cloud Computing-Google
https://cloud.google.com/products/
Compute Engine is Google’s Infrastructure-as-a-Service (IaaS).
App Engine is Google’s Platform-as-a-Service (PaaS).
Storage
Cloud SQL -a fully-managed, relational MySQL database.
Cloud Storage -a simple API that allows you to manage your data programmatically
Cloud Datastore provides a managed, NoSQL, schemaless database for storing non-relational data
Big Data
BigQuery. Run fast, SQL-like queries against multi-terabyte datasets in seconds
https://github.com/GoogleCloudPlatform

Cloud Computing-Amazon
http://aws.amazon.com/products/

More on Cloud Computing
Challenges and Opportunities for India (from
http://chennai.vit.ac.in/isbcc/)
http://www.slideshare.net/ajayohri/data-analytics-using-the-cloud-challenges-and-opportunities-for-india
Big Data Big Analytics (http://krishnarajpm.com/bigdata/abstract.pdf Workshop on
Statistical Machine Learning and Game Theory Approaches for Large Scale Data Analysis)
http://www.slideshare.net/ajayohri/big-data-big-analytics

R
http://www.r-project.org/
Open Source
Free
5000+ Packages
Growing Faster
>2 million users
RAM constraints??

R
Object Oriented
has GUI and IDE
has Commercial offerings

R - Rattle- Data Mining GUI
Object Oriented
has GUI and IDE

R - R Commander
Object Oriented
has GUI and IDE

R -Revolution Analytics
Free for Academics
World Wide !!
RevoScaleR package
for Big Data
Recommended Install -
http://info.revolutionanalytics.com/free-academic.html

R -Revolution Analytics
Free for Academics
World Wide !!
RevoScaleR package
for Big Data

My favorite places to learn R
http://www.swirlstats.com/

http://www.twotorials.com/

http://tryr.codeschool.com/

https://www.coursera.org/course/rprog
also see http://blog.datacamp.com/complete-list-of-coursera-courses-using-r-ranked-by-popularity/

R Case Study
Who are my Facebook friends?
Step 1
http://thinktostart.wordpress.com/2013/11/19/analyzing-facebook-with-r/
Step 2
https://gist.github.com/decisionstats/f18126aea544be324169

Case Study
my FB friends?
Step 1
http://thinktostart.wordpress.com/2013/11/19/analyzing-facebook-with-r/
Step 2
https://gist.github.com/decisionstats/f18126aea544be324169

Twitter Analysis
http://www.slideshare.net/ajayohri/twitter-analysis-by-kaify-rais
http://www.rdatamining.com/examples/social-network-analysis

Big Data Social Network Analysis
Analyzing A Big Social Network using R and distributed graph engines
http://thinkaurelius.com/2012/02/05/graph-degree-distributions-using-r-over-
hadoop/

Big Data Social Media Analysis
Can be used for Customers (and also for latent influencers) -http://www.r-
bloggers.com/an-example-of-social-network-analysis-with-r-using-package-igraph/

R package twitteR http://cran.r-project.org/web/packages/twitteR/index.html can
be used for prototyping but Twitter's API is rate limited to 1500 per hour(?)/day,
so we can use Datasift API http://datasift.com/pricing#costs

How does information propagate through a
social network?
http://www.r-bloggers.com/information-transmission-in-a-social-network-dissecting-the-spread-of-a-quora-post/

Big Data Social Network Analysis
Can be used for Terrorists (and also for potential protestors ) -Drew Conway http://riskecon.com/wp-
content/uploads/2012/02/Conway-Socio_Terrorism.pdf
Primary focus is one three aspects of network analysis
1. Identifying leadership and key actors
2. Revealing underlying structure and intra-network community structure
3. Evolution and decay of social networks

R -Big Data Packages
http://cran.r-project.org/web/views/HighPerformanceComputing.html
● The RHIPE package, started by Saptarshi Guha and now developed by a core team via GitHub, provides an interface
between R and Hadoop for analysis of large complex data wholly from within R using the Divide and Recombine approach
to big data. ( link )
● The rmr package by Revolution Analytics also provides an interface between R and Hadoop for a Map/Reduce
programming framework. ( link )
● A related package, segue package by Long, permits easy execution of embarassingly parallel task on Elastic Map Reduce
(EMR) at Amazon. ( link )
● The RProtoBuf package provides an interface to Google's language-neutral, platform-neutral, extensible mechanism for
serializing structured data. This package can be used in R code to read data streams from other systems in a distributed
MapReduce setting where data is serialized and passed back and forth between tasks.
● The HistogramTools package provides a number of routines useful for the construction, aggregation, manipulation, and
plotting of large numbers of Histograms such as those created by Mappers in a MapReduce application.

R -Hadoop Packages
https://github.com/RevolutionAnalytics/RHadoop/wiki
● plyrmr - higher level plyr-like data processing for structured data, powered by rmr
● rmr - functions providing Hadoop MapReduce functionality in R
● rhdfs - functions providing file management of the HDFS from within R
● rhbase - functions providing database management for the HBase distributed database from within R
http://amplab-extras.github.io/SparkR-pkg/
SparkR is an R package that provides a light-weight frontend to use Apache Spark from R.
https://github.com/nexr/RHive
RHive is an R extension facilitating distributed computing via HIVE query. RHive allows easy usage of HQL(Hive SQL) in R, and
allows easy usage of R objects and R functions in Hive.

R - Cloud Computing
http://cran.r-project.org/web/views/WebTechnologies.html

R -Big Data Packages
http://cran.r-project.org/web/views/HighPerformanceComputing.html
Large memory and out-of-memory data
● The biglm package by Lumley uses incremental computations to offer lm() and glm() functionality to data sets stored
outside of R's main memory.
● The ff package by Adler et al. offers file-based access to data sets that are too large to be loaded into memory, along with
a number of higher-level functions.
● The bigmemory package by Kane and Emerson permits storing large objects such as matrices in memory (as well as via
files) and uses external pointer objects to refer to them. .
● A large number of database packages, and database-alike packages (such as sqldf by Grothendieck and data.table
● The HadoopStreaming package provides a framework for writing map/reduce scripts for use in Hadoop Streaming; it also
facilitates operating on data in a streaming fashion which does not require Hadoop.
● The speedglm package permits to fit (generalised) linear models to large data.
● The biglars package by Seligman et al can use the ff to support large-than-memory datasets for least-angle regression,
lasso and stepwise regression.
● The bigrf package provides a Random Forests implementation with support for parellel execution and large memory.
● The MonetDB.R package allows R to access the MonetDB column-oriented, open source database system as a backend.

R in Finance
http://www.rinfinance.com/

R in Finance
http://www.quantmod.com/

C’est la vie
IN INDUSTRY - a R expert is one who knows which package to use from
IN RESEARCH- a R expert is one who creates a new popular and improved package

CRAN Views help experts
http://cran.r-project.org/web/views/

SAP with R
Departure of Aeroplanes-SAP Hana 200m
http://allthingsr.blogspot.in/#!/2012/04/big-data-r-and-hana-analyze-200-million.html
R using SAP Hana

SAP Hana DB uses R
http://scn.sap.com/community/in-memory-business-data-management/blog/2011/11/28/dealing-with-r-and-hana

Oracle R Enterprise
Case Studies and Examples
http://www.oracle.com/technetwork/database/options/advanced-analytics/r-enterprise/index.html

Oracle R Enterprise
Case Studies and Examples
http://www.oracle.com/technetwork/database/options/advanced-analytics/r-
enterprise/index.html

Additional
http://www.slideshare.net/ajayohri/open-source-analytics
Open Source in Analytics (OSSCamp 2014)
http://osscamp.in/
http://osscamp.in/events/6/open-source-analytics-overview-r-python-and-others

How does this affect
decision making
Lots of Data
IT is not a support function
Analytical Organizations with cross functional domains
and
Employees as first line of analysis
is education and research keeping up?

Lets do a revision
Requirements and People
a=NULL
a$req=c("Met","Unmet")
a$counts=c(50,50)
a=as.data.frame(a)
a
pie(a$counts,label=a$req)
library(RColorBrewer)
p=NULL
p$req=c("Satisfied","Unsatisfied","Busy Sleeping")
p$counts=c(50,40,10)
p=as.data.frame(p)
pie(p$counts,label=p$req,col=brewer.pal(3, "Set1"))

Thanks for listening
Contact - ohri2007@gmail.com
LinkedIN -http://linkedin.com/in/ajayohri
Questions please?

One more thing
a movie on a murdered IIM batchmate of mine
fighting against corruption just released
yesterday
http://www.imdb.com/title/tt3056632/

Decision making in the era of cloud computing and big data

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Decision making in the era of cloud computing and big data