Open source analytics

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how open source has helped analytics

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Open Source in Analytics

IntroductionIIML ,DCEFounder Decisionstats.comAuthor R for Business Analytics

Brief History of Analytics

SAS and SPSS led from 1970-s to early 2000sSAS leads market but very expensiveIBM bought SPSS but still not open source

R, Python and Hadoop Challenged this

Analytics Sub Components

Data StorageData QueryingData SummarizationData VisualizationStatistical Routines

Analytics Sub Components

Data StorageData QueryingData SummarizationData VisualizationStatistical Routines

*not an exhaustive list. Vendors provide a broader portfolio. Example purposes only.

Proprietary Open Source

OracleDBMSSQL Server

Business ObjectsSAP

SQL, SAS,Crystal Reports

Tableau

SAS,SPSS

Analytics Sub Components

Data StorageData QueryingData SummarizationData VisualizationStatistical Routines

*not an exhaustive list. Vendors provide a broader portfolio. Example purposes only.

Proprietary Open Source

OracleDBMSSQL Server

MySQL, NoSQL, Hadoop

Business ObjectsSAP

Pentaho, Jaspersoft

SQL, SAS,Crystal Reports

Still SQL,Pig, Hive

Tableau R,Python,Javascript

SAS,SPSS R,Python,RapidMiner

Analytics using Python

● pandas http://pandas.pydata.org/ High-performance, easy-to-use data structures and data analysis tools

● scikit-learn http://scikit-learn.org/stable/ Simple and efficient tools for data mining and data analysis and built on NumPy, SciPy, and matplotlib

● NumPy http://www.numpy.org/● SciPy http://www.scipy.org/scipylib/index.html● matplotlib http://matplotlib.org/

● statsmodels http://statsmodels.sourceforge.net/# Statsmodels is a Python module that allows users to

explore data, estimate statistical models, and perform statistical tests. An extensive list of descriptive statistics, statistical tests, plotting functions, and result statistics are available

● iPython http://ipython.org/ interactive computing

Analytics using Rhttp://www.r-project.org/

● RStudio and Revolution Analytics● sqldf https://code.google.com/p/sqldf/ and RODBC http://cran.r-project.org/web/packages/RODBC/index.html ● ggplot2 http://ggplot2.org/ and ggmap and shiny● RHadoop et al https://github.com/RevolutionAnalytics/RHadoop● car, stats, forecast, sna,tm● rattle and Rcommander (with plugins)

More at http://rforanalytics.wordpress.com/

Analytics using Rhttp://www.revolutionanalytics.com/

Analytics using Rhttp://www.revolutionanalytics.com/

Analytics using R<blatant self promotion>http://www.amazon.com/R-Business-Analytics-A-Ohri/dp/1461443423

R for Business Analytics looks at some of the most common tasks performed

by business analysts and helps the user navigate the wealth of information in R

and its packages. With this information the reader can select the packages that

can help process the analytical tasks with minimum effort and maximum usefulness

. The use of Graphical User Interfaces (GUI) is emphasized in this book to

further cut down and bend the famous learning curve in learning R.

</blatant self promotion>

Analytics using Rapid Miner

Early adopter of open source analyticsRecently moved from Germany to USA following PE infusionOne of the first marketplace for analytics extensions http://marketplace.rapid-i.com/UpdateServer/

One of the best GUI - Drag and Drop using flow

Analytics using Rapid Miner

Analytics using Jaspersoft

OLAPBIG DATA

(offered through cloud, mobile)

Analytics using Pentaho

Basically WekaReporting as wellComplete BI and Analytics Stack

Hadoop http://hadoop.apache.org/

Hadoop- evolving ecosystem

Hadoop- evolving ecosystem

Hadoop- evolving ecosystem

Rhttp://www.r-project.org/

Open Source

Free

5000+ Packages

Growing Faster

>2 million users

RAM constraints??

Rhttp://www.r-project.org/

Object Oriented

has GUI and IDE

has Commercial offerings

Rhttp://www.r-project.org/

Object Oriented

has GUI and IDE

has Commercial offerings

R - Rattle- Data Mining GUIhttp://www.r-project.org/

Object Oriented

has GUI and IDE

has Commercial offerings

R - R Commanderhttp://www.r-project.org/

Object Oriented

has GUI and IDE

has Commercial offerings

R -R Studio

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

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.

Terrific Data Mining using R GUI

Great Data Visualization using R GUI

So many packages- CRAN Views to the rescuehttp://cran.r-project.org/web/views/Bayesian Bayesian InferenceChemPhys Chemometrics and Computational PhysicsClinicalTrials Clinical Trial Design, Monitoring, and AnalysisCluster Cluster Analysis & Finite Mixture ModelsDifferentialEquations Differential EquationsDistributions Probability DistributionsEconometrics Computational EconometricsEnvironmetrics Analysis of Ecological and Environmental DataExperimentalDesign Design of Experiments (DoE) & Analysis of Experimental DataFinance Empirical FinanceGenetics Statistical GeneticsGraphics Graphic Displays & Dynamic Graphics & Graphic Devices & VisualizationHighPerformanceComputing High-Performance and Parallel Computing with RMachineLearning Machine Learning & Statistical LearningMedicalImaging Medical Image AnalysisMetaAnalysis Meta-AnalysisMultivariate Multivariate StatisticsNaturalLanguageProcessing Natural Language Processing

So many packages- CRAN Views to the rescuehttp://cran.r-project.org/web/views/NumericalMathematics Numerical MathematicsOfficialStatistics Official Statistics & Survey MethodologyOptimization Optimization and Mathematical ProgrammingPharmacokinetics Analysis of Pharmacokinetic DataPhylogenetics Phylogenetics, Especially Comparative MethodsPsychometrics Psychometric Models and MethodsReproducibleResearch Reproducible ResearchRobust Robust Statistical MethodsSocialSciences Statistics for the Social SciencesSpatial Analysis of Spatial DataSpatioTemporal Handling and Analyzing Spatio-Temporal DataSurvival Survival AnalysisTimeSeries Time Series Analysis WebTechnologies Web Technologies and ServicesgR gRaphical Models in R

R in the Browserhttp://www.r-fiddle.org/#/

http://statace.com/

http://www.rstudio.com/ide/server/

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 Computinghttp://cran.r-project.org/web/views/WebTechnologies.html

R -Big Data Packages http://cran.r-project.org/web/views/HighPerformanceComputing.htmlLarge 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.

Data Scientist Tool Kit

● web scraping● visualization● machine learning● data mining● modeling● sna● social media analytics

● web analytics● reproducible research ● TS forecasting ● spatial analysis● data storage ● data querying

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/

Linux https://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

Summary

Open source has greatly helped cut down cost of software in analyticsThe benefits of analytics continue to be manyAdded with Big Data and Cloud and MOOCs-----total cost to geeks is much lower !!

Thanks

Contact and Feedback-

ohri2007@gmail.com via http://linkedin.com/in/ajayohri

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