Protovis a graphical toolkit for visualization

I just found about a new data visualization tool called Protovis http://vis.stanford.edu/protovis/ex/

Protovis composes custom views of data with simple marks such as bars and dots. Unlike low-level graphics libraries that quickly become tedious for visualization, Protovis defines marks through dynamic properties that encode data, allowing inheritancescales and layouts to simplify construction.

Protovis is free and open-source and is a Stanford project. It has been used in web interface R Node (which I will talk later )

http://squirelove.net/r-node/doku.php

Conventional

While Protovis is designed for custom visualization, it is still easy to create many standard chart types. These simpler examples serve as an introduction to the language, demonstrating key abstractions such as quantitative and ordinal scales, while hinting at more advanced features, including stack layout.

Custom

Many charting libraries provide stock chart designs, but offer only limited customization; Protovis excels at custom visualization design through a concise representation and precise control over graphical marks. These examples, including a few recreations of unusual historical designs, demonstrate the language’s expressiveness.

 

 

Try Protovis today 🙂 http://vis.stanford.edu/protovis/

It uses JavaScript and SVG for web-native visualizations; no plugin required (though you will need a modern web browser)! Although programming experience is helpful, Protovis is mostly declarative and designed to be learned by example.

Viva Libre Office

WordPerfect 5.1 for DOS.
Image via Wikipedia

The Document Foundation is happy to announce the release candidate of
LibreOffice 3.3.1. This release candidate is the first in a series of
frequent bugfix releases on top of our LibreOffice 3.3 product. Please
be aware that LibreOffice 3.3.1 RC1 is not yet ready for production
use, you should continue to use LibreOffice for that.

http://listarchives.documentfoundation.org/www/announce/msg00028.html

Following is the list of changes against LibreOffice 3.3:

Key changes at a glance:

* Numerous translation updates
* new mimetype icons for LibreOffice – explained here:
http://luxate.blogspot.com/2011/01/not-even-included-but-already-improved.html
* quite a few crasher fixes

Detailed change log:

* translation updates
* Removed old/unmaintained icon themes
* Fix for https://bugzilla.novell.com/show_bug.cgi?id=664516: Don’t
use a reference or the default formula string will be changed
* Install bash completion for oo* wrappers when enabled
(https://bugzilla.novell.com/show_bug.cgi?id=665402)
* Build fix: get the stlport compat workaround working for gcc 4.6.0
* Build fix: no ddraw.h or ddraw.lib in the June 2010 DirectX SDK,
removed usage
* Windows installer: padded nologobanner.bmp, new size is 102×58
* removed gd – Gaelic, ky – Kirghiz, pap – Papiamento, ti – Tigrinya,
ms – Malay, ps – Pashto, ur – Urdu. UI localization does not exist
in these languages. So it makes no sense to ship packages.
* Build fix: pass thru PYTHON, found by configure. Will be used by
filter/source/config/fragments/makefile.mk.
* Upgraded libwpd (WordPerfect filter) to 0.9.1
* Fixed BrOffice Windows start menu branding
* Removed language code ‘kid’. kid is not Koshin, but key id pseudo
language which is good for debugging UI but should no be included
in the product
* Added ca_XV and ast language/local name and description
* Fixed incorrect page number in page preview mode
(https://bugs.freedesktop.org/show_bug.cgi?id=33155). When the
window is large enough to show several ‘Page X’ strings,
the page number was not properly incremented.
* Fixed incorrect import of cell attributes from Excel
documents. When a cell with non-default formatting attribute starts
with non-first row in a column, the filter would incorrectly apply
the same format to all the cells above it if they didn’t have any
formats.
* Ubuntu: fix for lp#696527 – enable human icon theme in LibreOffice
* Fix for https://bugzilla.redhat.com/show_bug.cgi?id=673819 crash on
changing position of drawing object in header.
* Changed OpenOffice.org to LibreOffice in nsplugin
* Added Occitan dictionary
* Added Ukrainian dictionaries
* Fix window focus for langpack installation on Mac –
https://bugs.freedesktop.org/show_bug.cgi?id=33056
* Added/modified NLPsolver translations from Pootle
* Fix for https://bugzilla.novell.com/show_bug.cgi?id=655763
* Fix for RTF export crasher
(https://bugzilla.novell.com/show_bug.cgi?id=656503)
* Use LibreOffice as product name for EPS Creator header
* Parse svg ‘color’ property (fixes
https://bugs.freedesktop.org/show_bug.cgi?id=33551)
* Use double instead of float in writerfilter import
* Build fix: use PYTHON as passed through by set_soenv.in.
* Fix for https://bugs.freedesktop.org/show_bug.cgi?id=33237 remove
debug line
* Fix for https://bugs.freedesktop.org/show_bug.cgi?id=33237 – fixes
ole object import for writer (docx)
* Fix for https://bugs.freedesktop.org/show_bug.cgi?id=33249
rename OOo -> LibO on Getting Support Page
* Fix ooxml import: handle css::table::BorderLine in addition to
css::table::BorderLine2 That means that table cell properties are
correctly set on import again.
* Fix for https://bugs.freedesktop.org/show_bug.cgi?id=33258
wikihelp: Improve the check for existence of the localized help.
* Fix for https://bugs.freedesktop.org/show_bug.cgi?id=33994 – fixes
several crashes around config UNO API
* Fix for https://bugs.freedesktop.org/show_bug.cgi?id=30879
* Fix for https://bugs.freedesktop.org/show_bug.cgi?id=32872
Implementation names weren’t matching with xcu.
* Fix: don’t pushback and process a corrupt extension
* Fix: wikihelp – do not check for existence of the localized
help. In case we do not have the help installed, it is up to the
online service to decide the fallback in case a language version is
not available.
* Fix README: change su urpmi to sudo urpmi for Mandriva section
* Fix README formatting –
https://bugs.freedesktop.org/show_bug.cgi?id=32741 – using CRLF
instead of LF on WIN platform
* Fix README: word wrap at column 75 for better readability
* Build fix: KDE3 library search order
(https://bugs.freedesktop.org/show_bug.cgi?id=32797). Use LINKFLAGS
instead of STDLIBS.
* Start using technical.dic instead of oracle.dic
(https://bugs.freedesktop.org/show_bug.cgi?id=31798)
* Build fix: add explicit QRegion* for clipRegion to fix compile of
kde backend
* Cleanup: removed obsolete m_bSingleAltPress
* Remove the menu when Left Alt Key was pressed for GTK
* Fix for https://bugs.freedesktop.org/show_bug.cgi?id=33459: use
year of era in long format for zh_TW by default
* Fix wrong collation for Catalan language
* Fix for https://bugs.freedesktop.org/show_bug.cgi?id=31271 wrong
line break with “(”
* Fix for https://bugs.freedesktop.org/show_bug.cgi?id=32561 – crash
when iterating over the database types.
* Default currency for Estonia should be Euro – fixes
https://bugs.freedesktop.org/show_bug.cgi?id=33160
* Avoid a pointless GetHelpText() call in the toolbox. Fixes
https://bugs.freedesktop.org/show_bug.cgi?id=33315. GetHelpText()
can be quite heavy, see
https://bugs.freedesktop.org/show_bug.cgi?id=33088.
* Paint toolbar handle positioned properly
(https://bugs.freedesktop.org/show_bug.cgi?id=32558)
* Build fix: move cxxabi.h after stl headers to workaround gcc 4.6.0
and stlport
* Fix for https://bugs.freedesktop.org/show_bug.cgi?id=33355
manipulate also the C runtime’s environment
* Fix for CTL/Other Default Font #i25247#, #i25561#, #i48064#,
#i92341#
* RTF export crasher
(https://bugzilla.novell.com/show_bug.cgi?id=656503)
* Fixed an infinite loop in RTF exporter
* UI: translations need more space on word count dialog, made space
for it.
* Fix for https://bugzilla.novell.com/show_bug.cgi?id=660816 improve
formfield checkbox binary export (and import)

Again a BIG Thank You!

Again whats Libre Office

What does LibreOffice give you?

Writer is the word processor inside LibreOffice. Use it for everything, from dashing off a quick letter to producing an entire book with tables of contents, embedded illustrations, bibliographies and diagrams. The while-you-type auto-completion, auto-formatting and automatic spelling checking make difficult tasks easy (but are easy to disable if you prefer). Writer is powerful enough to tackle desktop publishing tasks such as creating multi-column newsletters and brochures. The only limit is your imagination.

Calc tames your numbers and helps with difficult decisions when you’re weighing the alternatives. Analyze your data with Calc and then use it to present your final output. Charts and analysis tools help bring transparency to your conclusions. A fully-integrated help system makes easier work of entering complex formulas. Add data from external databases such as SQL or Oracle, then sort and filter them to produce statistical analyses. Use the graphing functions to display large number of 2D and 3D graphics from 13 categories, including line, area, bar, pie, X-Y, and net – with the dozens of variations available, you’re sure to find one that suits your project.

Impress is the fastest and easiest way to create effective multimedia presentations. Stunning animation and sensational special effects help you convince your audience. Create presentations that look even more professional than the standard presentations you commonly see at work. Get your collegues’ and bosses’ attention by creating something a little bit different.

Draw lets you build diagrams and sketches from scratch. A picture is worth a thousand words, so why not try something simple with box and line diagrams? Or else go further and easily build dynamic 3D illustrations and special effects. It’s as simple or as powerful as you want it to be.

Base is the database front-end of the LibreOffice suite. With Base, you can seamlessly integrate your existing database structures into the other components of LibreOffice, or create an interface to use and administer your data as a stand-alone application. You can use imported and linked tables and queries from MySQL, PostgreSQL or Microsoft Access and many other data sources, or design your own with Base, to build powerful front-ends with sophisticated forms, reports and views. Support is built-in or easily addable for a very wide range of database products, notably the standardly-provided HSQL, MySQL, Adabas D, Microsoft Access and PostgreSQL.

Math is a simple equation editor that lets you lay-out and display your mathematical, chemical, electrical or scientific equations quickly in standard written notation. Even the most-complex calculations can be understandable when displayed correctly. E=mc2.

LibreOffice also comes configured with a PDF file creator, meaning you can distribute documents that you’re sure can be opened and read by users of almost any computing device or operating system.

Download LibreOffice now and try it out today.

http://www.libreoffice.org/features/

 

Lyx Releases 2

Ubuntu Login
Image via Wikipedia

Lyx releases new version- now if only there was a SIMPLE way to put R code in a Lyx existing text class (having tried Sweave and sweaved myself into knots ! 😦

and I hope Ubuntu Linux 10.10  netbook fixes the curious case of disappearing menu bar in Lyx

see https://bugs.launchpad.net/ubuntu/+source/indicator-appmenu/+bug/619811

(Hint start Lyx using from the terminal:
QT_X11_NO_NATIVE_MENUBAR=1 lyx)

Latest News from the

http://www.lyx.org/News#item2

We are pleased to announce the release of LyX 1.6.9

 

Beta Release: LyX 2.0.0 beta 4 released.

February 6, 2011

We are pleased to announce the fourth public pre-release of LyX 2.0.0.
Except usual bugfixing we fixed random crashes connected with the new background export and compilation feature.

As far as new features is considered it is now possible

  • to set the table width,
  • customize the language package per document,
  • export LyX files as a single archive containing linked material (e.g. images) directly via export menu.

 

Since this is most probably the last beta release we also added convertor for old (1.6) preference files which are automatically checked on the startup now.

 

Windows Azure and Amazon Free offer

Simple Cpu Cache Memory Organization
Image via Wikipedia

For Hi-Computing folks try out Azure for free-

http://www.microsoft.com/windowsazure/offers/popup/popup.aspx?lang=en&locale=en-US&offer=MS-AZR-0001P#compute

Windows Azure Platform
Introductory Special

This promotional offer enables you to try a limited amount of the Windows Azure platform at no charge. The subscription includes a base level of monthly compute hours, storage, data transfers, a SQL Azure database, Access Control transactions and Service Bus connections at no charge. Please note that any usage over this introductory base level will be charged at standard rates.

Included each month at no charge:

  • Windows Azure
    • 25 hours of a small compute instance
    • 500 MB of storage
    • 10,000 storage transactions
  • SQL Azure
    • 1GB Web Edition database (available for first 3 months only)
  • Windows Azure platform AppFabric
    • 100,000 Access Control transactions
    • 2 Service Bus connections
  • Data Transfers (per region)
    • 500 MB in
    • 500 MB out

Any monthly usage in excess of the above amounts will be charged at the standard rates. This introductory special will end on March 31, 2011 and all usage will then be charged at the standard rates.

Standard Rates:

Windows Azure

  • Compute*
    • Extra small instance**: $0.05 per hour
    • Small instance (default): $0.12 per hour
    • Medium instance: $0.24 per hour
    • Large instance: $0.48 per hour
    • Extra large instance: $0.96 per hour

 

http://aws.amazon.com/ec2/pricing/

Free Tier*

As part of AWS’s Free Usage Tier, new AWS customers can get started with Amazon EC2 for free. Upon sign-up, new AWScustomers receive the following EC2 services each month for one year:

  • 750 hours of EC2 running Linux/Unix Micro instance usage
  • 750 hours of Elastic Load Balancing plus 15 GB data processing
  • 10 GB of Amazon Elastic Block Storage (EBS) plus 1 million IOs, 1 GB snapshot storage, 10,000 snapshot Get Requests and 1,000 snapshot Put Requests
  • 15 GB of bandwidth in and 15 GB of bandwidth out aggregated across all AWS services

 

Paid Instances-

 

Standard On-Demand Instances Linux/UNIX Usage Windows Usage
Small (Default) $0.085 per hour $0.12 per hour
Large $0.34 per hour $0.48 per hour
Extra Large $0.68 per hour $0.96 per hour
Micro On-Demand Instances
Micro $0.02 per hour $0.03 per hour
High-Memory On-Demand Instances
Extra Large $0.50 per hour $0.62 per hour
Double Extra Large $1.00 per hour $1.24 per hour
Quadruple Extra Large $2.00 per hour $2.48 per hour
High-CPU On-Demand Instances
Medium $0.17 per hour $0.29 per hour
Extra Large $0.68 per hour $1.16 per hour
Cluster Compute Instances
Quadruple Extra Large $1.60 per hour N/A*
Cluster GPU Instances
Quadruple Extra Large $2.10 per hour N/A*
* Windows is not currently available for Cluster Compute or Cluster GPU Instances.

 

NOTE- Amazon Instance definitions differ slightly from Azure definitions

http://aws.amazon.com/ec2/instance-types/

Available Instance Types

Standard Instances

Instances of this family are well suited for most applications.

Small Instance – default*

1.7 GB memory
1 EC2 Compute Unit (1 virtual core with 1 EC2 Compute Unit)
160 GB instance storage
32-bit platform
I/O Performance: Moderate
API name: m1.small

Large Instance

7.5 GB memory
4 EC2 Compute Units (2 virtual cores with 2 EC2 Compute Units each)
850 GB instance storage
64-bit platform
I/O Performance: High
API name: m1.large

Extra Large Instance

15 GB memory
8 EC2 Compute Units (4 virtual cores with 2 EC2 Compute Units each)
1,690 GB instance storage
64-bit platform
I/O Performance: High
API name: m1.xlarge

Micro Instances

Instances of this family provide a small amount of consistent CPU resources and allow you to burst CPU capacity when additional cycles are available. They are well suited for lower throughput applications and web sites that consume significant compute cycles periodically.

Micro Instance

613 MB memory
Up to 2 EC2 Compute Units (for short periodic bursts)
EBS storage only
32-bit or 64-bit platform
I/O Performance: Low
API name: t1.micro

High-Memory Instances

Instances of this family offer large memory sizes for high throughput applications, including database and memory caching applications.

High-Memory Extra Large Instance

17.1 GB of memory
6.5 EC2 Compute Units (2 virtual cores with 3.25 EC2 Compute Units each)
420 GB of instance storage
64-bit platform
I/O Performance: Moderate
API name: m2.xlarge

High-Memory Double Extra Large Instance

34.2 GB of memory
13 EC2 Compute Units (4 virtual cores with 3.25 EC2 Compute Units each)
850 GB of instance storage
64-bit platform
I/O Performance: High
API name: m2.2xlarge

High-Memory Quadruple Extra Large Instance

68.4 GB of memory
26 EC2 Compute Units (8 virtual cores with 3.25 EC2 Compute Units each)
1690 GB of instance storage
64-bit platform
I/O Performance: High
API name: m2.4xlarge

High-CPU Instances

Instances of this family have proportionally more CPU resources than memory (RAM) and are well suited for compute-intensive applications.

High-CPU Medium Instance

1.7 GB of memory
5 EC2 Compute Units (2 virtual cores with 2.5 EC2 Compute Units each)
350 GB of instance storage
32-bit platform
I/O Performance: Moderate
API name: c1.medium

High-CPU Extra Large Instance

7 GB of memory
20 EC2 Compute Units (8 virtual cores with 2.5 EC2 Compute Units each)
1690 GB of instance storage
64-bit platform
I/O Performance: High
API name: c1.xlarge

Cluster Compute Instances

Instances of this family provide proportionally high CPU resources with increased network performance and are well suited for High Performance Compute (HPC) applications and other demanding network-bound applications. Learn more about use of this instance type for HPC applications.

Cluster Compute Quadruple Extra Large Instance

23 GB of memory
33.5 EC2 Compute Units (2 x Intel Xeon X5570, quad-core “Nehalem” architecture)
1690 GB of instance storage
64-bit platform
I/O Performance: Very High (10 Gigabit Ethernet)
API name: cc1.4xlarge

Cluster GPU Instances

Instances of this family provide general-purpose graphics processing units (GPUs) with proportionally high CPU and increased network performance for applications benefitting from highly parallelized processing, including HPC, rendering and media processing applications. While Cluster Compute Instances provide the ability to create clusters of instances connected by a low latency, high throughput network, Cluster GPU Instances provide an additional option for applications that can benefit from the efficiency gains of the parallel computing power of GPUs over what can be achieved with traditional processors. Learn moreabout use of this instance type for HPC applications.

Cluster GPU Quadruple Extra Large Instance

22 GB of memory
33.5 EC2 Compute Units (2 x Intel Xeon X5570, quad-core “Nehalem” architecture)
2 x NVIDIA Tesla “Fermi” M2050 GPUs
1690 GB of instance storage
64-bit platform
I/O Performance: Very High (10 Gigabit Ethernet)
API name: cg1.4xlarge

versus-

Windows Azure compute instances come in five unique sizes to enable complex applications and workloads.

Compute Instance Size CPU Memory Instance Storage I/O Performance
Extra Small 1 GHz 768 MB 20 GB* Low
Small 1.6 GHz 1.75 GB 225 GB Moderate
Medium 2 x 1.6 GHz 3.5 GB 490 GB High
Large 4 x 1.6 GHz 7 GB 1,000 GB High
Extra large 8 x 1.6 GHz 14 GB 2,040 GB High

*There is a limitation on the Virtual Hard Drive (VHD) size if you are deploying a Virtual Machine role on an extra small instance. The VHD can only be up to 15 GB.

 

 

Challenges of Analyzing a dataset (with R)

GIF-animation showing a moving echocardiogram;...
Image via Wikipedia

Analyzing data can have many challenges associated with it. In the case of business analytics data, these challenges or constraints can have a marked effect on the quality and timeliness of the analysis as well as the expected versus actual payoff from the analytical results.

Challenges of Analytical Data Processing-

1) Data Formats- Reading in complete data, without losing any part (or meta data), or adding in superfluous details (that increase the scope). Technical constraints of data formats are relatively easy to navigate thanks to ODBC and well documented and easily search-able syntax and language.

The costs of additional data augmentation (should we pay for additional credit bureau data to be appended) , time of storing and processing the data (every column needed for analysis can add in as many rows as whole dataset, which can be a time enhancing problem if you are considering an extra 100 variables with a few million rows), but above all that of business relevance and quality guidelines will ensure basic data input and massaging are considerable parts of whole analytical project timeline.

2) Data Quality-Perfect data exists in a perfect world. The price of perfect information is one business will mostly never budget or wait for. To deliver inferences and results based on summaries of data which has missing, invalid, outlier data embedded within it makes the role of an analyst just as important as which ever tool is chosen to remove outliers, replace missing values, or treat invalid data.

3) Project Scope-

How much data? How much Analytical detail versus High Level Summary? Timelines for delivery as well as refresh of data analysis? Checks (statistical as well as business)?

How easy is it to load and implement the new analysis in existing Information Technology Infrastructure? These are some of the outer parameters that can limit both your analytical project scope, your analytical tool choice, and your processing methodology.
4) Output Results vis a vis stakeholder expectation management-

Stakeholders like to see results, not constraints, hypothesis ,assumptions , p-value, or chi -square value. Output results need to be streamlined to a decision management process to justify the investment of human time and effort in an analytical project, choice,training and navigating analytical tool complexities and constraints are subset of it. Optimum use of graphical display is a part of aligning results to a more palatable form to stakeholders, provided graphics are done nicely.

Eg Marketing wants to get more sales so they need a clear campaign, to target certain customers via specific channels with specified collateral. In order to base their business judgement, business analytics needs to validate , cross validate and sometimes invalidate this business decision making with clear transparent methods and processes.

Given a dataset- the basic analytical steps that an analyst will do with R are as follows. This is meant as a note for analysts at a beginner level with R.

Package -specific syntax

update.packages() #This updates all packages
install.packages(package1) #This installs a package locally, a one time event
library(package1) #This loads a specified package in the current R session, which needs to be done every R session

CRAN________LOCAL HARD DISK_________R SESSION is the top to bottom hierarchy of package storage and invocation.

ls() #This lists all objects or datasets currently active in the R session

> names(assetsCorr)  #This gives the names of variables within a dataframe
[1] “AssetClass”            “LargeStocksUS”         “SmallStocksUS”
[4] “CorporateBondsUS”      “TreasuryBondsUS”       “RealEstateUS”
[7] “StocksCanada”          “StocksUK”              “StocksGermany”
[10] “StocksSwitzerland”     “StocksEmergingMarkets”

> str(assetsCorr) #gives complete structure of dataset
‘data.frame’:    12 obs. of  11 variables:
$ AssetClass           : Factor w/ 12 levels “CorporateBondsUS”,..: 4 5 2 6 1 12 3 7 11 9 …
$ LargeStocksUS        : num  15.3 16.4 1 0 0 …
$ SmallStocksUS        : num  13.49 16.64 0.66 1 0 …
$ CorporateBondsUS     : num  9.26 6.74 0.38 0.46 1 0 0 0 0 0 …
$ TreasuryBondsUS      : num  8.44 6.26 0.33 0.27 0.95 1 0 0 0 0 …
$ RealEstateUS         : num  10.6 17.32 0.08 0.59 0.35 …
$ StocksCanada         : num  10.25 19.78 0.56 0.53 -0.12 …
$ StocksUK             : num  10.66 13.63 0.81 0.41 0.24 …
$ StocksGermany        : num  12.1 20.32 0.76 0.39 0.15 …
$ StocksSwitzerland    : num  15.01 20.8 0.64 0.43 0.55 …
$ StocksEmergingMarkets: num  16.5 36.92 0.3 0.6 0.12 …

> dim(assetsCorr) #gives dimensions observations and variable number
[1] 12 11

str(Dataset) – This gives the structure of the dataset (note structure gives both the names of variables within dataset as well as dimensions of the dataset)

head(dataset,n1) gives the first n1 rows of dataset while
tail(dataset,n2) gives the last n2 rows of a dataset where n1,n2 are numbers and dataset is the name of the object (here a data frame that is being considered)

summary(dataset) gives you a brief summary of all variables while

library(Hmisc)
describe(dataset) gives a detailed description on the variables

simple graphics can be given by

hist(Dataset1)
and
plot(Dataset1)

As you can see in above cases, there are multiple ways to get even basic analysis about data in R- however most of the syntax commands are intutively understood (like hist for histogram, t.test for t test, plot for plot).

For detailed analysis throughout the scope of analysis, for a business analytics user it is recommended to using multiple GUI, and multiple packages. Even for highly specific and specialized analytical tasks it is recommended to check for a GUI that incorporates the required package.

Interview Ajay Ohri Decisionstats.com with DMR

From-

http://www.dataminingblog.com/data-mining-research-interview-ajay-ohri/

Here is the winner of the Data Mining Research People Award 2010: Ajay Ohri! Thanks to Ajay for giving some time to answer Data Mining Research questions. And all the best to his blog, Decision Stat!

Data Mining Research (DMR): Could you please introduce yourself to the readers of Data Mining Research?

Ajay Ohri (AO): I am a business consultant and writer based out of Delhi- India. I have been working in and around the field of business analytics since 2004, and have worked with some very good and big companies primarily in financial analytics and outsourced analytics. Since 2007, I have been writing my blog at http://decisionstats.com which now has almost 10,000 views monthly.

All in all, I wrote about data, and my hobby is also writing (poetry). Both my hobby and my profession stem from my education ( a masters in business, and a bachelors in mechanical engineering).

My research interests in data mining are interfaces (simpler interfaces to enable better data mining), education (making data mining less complex and accessible to more people and students), and time series and regression (specifically ARIMAX)
In business my research interests software marketing strategies (open source, Software as a service, advertising supported versus traditional licensing) and creation of technology and entrepreneurial hubs (like Palo Alto and Research Triangle, or Bangalore India).

DMR: I know you have worked with both SAS and R. Could you give your opinion about these two data mining tools?

AO: As per my understanding, SAS stands for SAS language, SAS Institute and SAS software platform. The terms are interchangeably used by people in industry and academia- but there have been some branding issues on this.
I have not worked much with SAS Enterprise Miner , probably because I could not afford it as business consultant, and organizations I worked with did not have a budget for Enterprise Miner.
I have worked alone and in teams with Base SAS, SAS Stat, SAS Access, and SAS ETS- and JMP. Also I worked with SAS BI but as a user to extract information.
You could say my use of SAS platform was mostly in predictive analytics and reporting, but I have a couple of projects under my belt for knowledge discovery and data mining, and pattern analysis. Again some of my SAS experience is a bit dated for almost 1 year ago.

I really like specific parts of SAS platform – as in the interface design of JMP (which is better than Enterprise Guide or Base SAS ) -and Proc Sort in Base SAS- I guess sequential processing of data makes SAS way faster- though with computing evolving from Desktops/Servers to even cheaper time shared cloud computers- I am not sure how long Base SAS and SAS Stat can hold this unique selling proposition.

I dislike the clutter in SAS Stat output, it confuses me with too much information, and I dislike shoddy graphics in the rendering output of graphical engine of SAS. Its shoddy coding work in SAS/Graph and if JMP can give better graphics why is legacy source code preventing SAS platform from doing a better job of it.

I sometimes think the best part of SAS is actually code written by Goodnight and Sall in 1970’s , the latest procs don’t impress me much.

SAS as a company is something I admire especially for its way of treating employees globally- but it is strange to see the rest of tech industry not following it. Also I don’t like over aggression and the SAS versus Rest of the Analytics /Data Mining World mentality that I sometimes pick up when I deal with industry thought leaders.

I think making SAS Enterprise Miner, JMP, and Base SAS in a completely new web interface priced at per hour rates is my wishlist but I guess I am a bit sentimental here- most data miners I know from early 2000’s did start with SAS as their first bread earning software. Also I think SAS needs to be better priced in Business Intelligence- it seems quite cheap in BI compared to Cognos/IBM but expensive in analytical licensing.

If you are a new stats or business student, chances are – you may know much more R than SAS today. The shift in education at least has been very rapid, and I guess R is also more of a platform than a analytics or data mining software.

I like a lot of things in R- from graphics, to better data mining packages, modular design of software, but above all I like the can do kick ass spirit of R community. Lots of young people collaborating with lots of young to old professors, and the energy is infectious. Everybody is a CEO in R ’s world. Latest data mining algols will probably start in R, published in journals.

Which is better for data mining SAS or R? It depends on your data and your deadline. The golden rule of management and business is -it depends.

Also I have worked with a lot of KXEN, SQL, SPSS.

DMR: Can you tell us more about Decision Stats? You have a traffic of 120′000 for 2010. How did you reach such a success?

AO: I don’t think 120,000 is a success. Its not a failure. It just happened- the more I wrote, the more people read.In 2007-2008 I used to obsess over traffic. I tried SEO, comments, back linking, and I did some black hat experimental stuff. Some of it worked- some didn’t.

In the end, I started asking questions and interviewing people. To my surprise, senior management is almost always more candid , frank and honest about their views while middle managers, public relations, marketing folks can be defensive.

Social Media helped a bit- Twitter, Linkedin, Facebook really helped my network of friends who I suppose acted as informal ambassadors to spread the word.
Again I was constrained by necessity than choices- my middle class finances ( I also had a baby son in 2007-my current laptop still has some broken keys :) – by my inability to afford traveling to conferences, and my location Delhi isn’t really a tech hub.

The more questions I asked around the internet, the more people responded, and I wrote it all down.

I guess I just was lucky to meet a lot of nice people on the internet who took time to mentor and educate me.

I tried building other websites but didn’t succeed so i guess I really don’t know. I am not a smart coder, not very clever at writing but I do try to be honest.

Basic economics says pricing is proportional to demand and inversely proportional to supply. Honest and candid opinions have infinite demand and an uncertain supply.

DMR: There is a rumor about a R book you plan to publish in 2011 :-) Can you confirm the rumor and tell us more?

AO: I just signed a contract with Springer for ” R for Business Analytics”. R is a great software, and lots of books for statistically trained people, but I felt like writing a book for the MBAs and existing analytics users- on how to easily transition to R for Analytics.

Like any language there are tricks and tweaks in R, and with a focus on code editors, IDE, GUI, web interfaces, R’s famous learning curve can be bent a bit.

Making analytics beautiful, and simpler to use is always a passion for me. With 3000 packages, R can be used for a lot more things and a lot more simply than is commonly understood.
The target audience however is business analysts- or people working in corporate environments.

Brief Bio-
Ajay Ohri has been working in the field of analytics since 2004 , when it was a still nascent emerging Industries in India. He has worked with the top two Indian outsourcers listed on NYSE,and with Citigroup on cross sell analytics where he helped sell an extra 50000 credit cards by cross sell analytics .He was one of the very first independent data mining consultants in India working on analytics products and domestic Indian market analytics .He regularly writes on analytics topics on his web site www.decisionstats.com and is currently working on open source analytical tools like R besides analytical software like SPSS and SAS.