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.

Brief Interview Timo Elliott

Here is a brief interview with Timo Elliott.Timo Elliott is a 19-year veteran of SAP Business Objects.

Ajay- What are the top 5 events in Business Integration and Data Visualization services you saw in 2010 and what are the top three trends you see in these in 2011.


Timo-

Top five events in 2010:

(1) Back to strong market growth. IT spending plummeted last year (BI continued to grow, but more slowly than previous years). This year, organizations reopened their wallets and funded new analytics initiatives — all the signs indicate that BI market growth will be double that of 2009.

(2) The launch of the iPad. Mobile BI has been around for years, but the iPad opened the floodgates of organizations taking a serious look at mobile analytics — and the easy-to-use, executive-friendly iPad dashboards have considerably raised the profile of analytics projects inside organizations.

(3) Data warehousing got exciting again. Decades of incremental improvements (column databases, massively parallel processing, appliances, in-memory processing…) all came together with robust commercial offers that challenged existing data storage and calculation methods. And new “NoSQL” approaches, designed for the new problems of massive amounts of less-structured web data, started moving into the mainstream.

(4) The end of Google Wave, the start of social BI.Google Wave was launched as a rethink of how we could bring together email, instant messaging, and social networks. While Google decided to close down the technology this year, it has left its mark, notably by influencing the future of “social BI”, with several major vendors bringing out commercial products this year.

(5) The start of the big BI merge. While several small independent BI vendors reported strong growth, the major trend of the year was consolidation and integration: the BI megavendors (SAP, Oracle, IBM, Microsoft) increased their market share (sometimes by acquiring smaller vendors, e.g. IBM/SPSS and SAP/Sybase) and integrated analytics with their existing products, blurring the line between BI and other technology areas.

Top three trends next year:

(1) Analytics, reinvented. New DW techniques make it possible to do sub-second, interactive analytics directly against row-level operational data. Now BI processes and interfaces need to be rethought and redesigned to make best use of this — notably by blurring the distinctions between the “design” and “consumption” phases of BI.

(2) Corporate and personal BI come together. The ability to mix corporate and personal data for quick, pragmatic analysis is a common business need. The typical solution to the problem — extracting and combining the data into a local data store (either Excel or a departmental data mart) — pleases users, but introduces duplication and extra costs and makes a mockery of information governance. 2011 will see the rise of systems that let individuals and departments load their data into personal spaces in the corporate environment, allowing pragmatic analytic flexibility without compromising security and governance.

(3) The next generation of business applications. Where are the business applications designed to support what people really do all day, such as implementing this year’s strategy, launching new products, or acquiring another company? 2011 will see the first prototypes of people-focused, flexible, information-centric, and collaborative applications, bringing together the best of business intelligence, “enterprise 2.0”, and existing operational applications.

And one that should happen, but probably won’t:

(4) Intelligence = Information + PEOPLE. Successful analytics isn’t about technology — it’s about people, process, and culture. The biggest trend in 2011 should be organizations spending the majority of their efforts on user adoption rather than technical implementation.                 About- http://timoelliott.com/blog/about

Timo Elliott is a 19-year veteran of SAP BusinessObjects, and has spent the last twenty years working with customers around the world on information strategy.

He works closely with SAP research and innovation centers around the world to evangelize new technology prototypes.

His popular Business Analytics and SAPWeb20 blogs track innovation in analytics and social media, including topics such as augmented corporate reality, collaborative decision-making, and social network analysis.

His PowerPoint Twitter Tools lets presenters see and react to tweets in real time, embedded directly within their slides.

A popular and engaging speaker, Elliott presents regularly to IT and business audiences at international conferences, on subjects such as why BI projects fail and what to do about it, and the intersection of BI and enterprise 2.0.

Prior to Business Objects, Elliott was a computer consultant in Hong Kong and led analytics projects for Shell in New Zealand. He holds a first-class honors degree in Economics with Statistics from Bristol University, England. He blogs on http://timoelliott.com/blog/ (one of the best designed blogs in BI) . You can see more about him personal web site here and photo/sketch blog here. You should follow Timo at http://twitter.com/timoelliott

Art Credit- Timo Elliott

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Reputation on Social Networks

Law of Diminishing Marginal Utility
Image via Wikipedia

Classical Economics talks of the value of utlity, diminishing marginal utility if the same things is repeated again and again (like spam in an online community)

StackOverflow has a great way of measuring reputation – and thus allows intangible benefits /awards -similar to wikipedia badges , reddit karma. Utility is also auto generated like @klout  on twitter or lists memberships and other sucessful open source communities online including Ubuntu forums have ways to create ah hierarchies even in class less utopian classes.

Basically it then acts as the motivating game as the mostly boy population try to race on numbers.

 

in Stack Overflow- you can get buddies to upvote you and basically act as a role playing game too.

—–From http://stackoverflow.com/faq#reputation

To gain reputation, post good questions and useful answers. Your peers will vote on your posts, and those votes will cause you to gain (or, in rare cases, lose) reputation:

answer is voted up +10
question is voted up +5
answer is accepted +15 (+2 to acceptor)
post is voted down -2 (-1 to voter)

A maximum of 30 votes can be cast per user per day, and you can earn a maximum of 200 reputation per day (although accepted answers and bounty awards are immune to this limit). Also, please note that votes for any posts marked “community wiki” do not generate reputation.

Amass enough reputation points and Stack Overflow will allow you to go beyond simply asking and answering questions:

15 Vote up
15 Flag offensive
50 Leave comments
100 Edit community wiki posts
125 Vote down (costs 1 rep)
200 Reduced advertising

New Deal in Statistical Training

The United States Government is planning a new initiative at providing employable skills to people, to cope with unemployment.
One skill perpetually in shortage is analytics training along with skills in statistics.

It is time that corporates like IBM SPSS, SAS Institute and Revolution Analytics as well as offshore companies in India or Asia can ramp up their on demand trainings, certification as well as academic partnership bundles. Indeed offshroing companies can earn revenue as well as goodwill if they help in with trainers available via video- conferencing. The new Deal initiative would require creative thinking as well as direct top management support to focus their best internal brains at developing this new revenue stream. Again the company that trains the most users (be it Revolution for R, IBM for SPSS-Cognos, SAS Institute for Base SAS-JMP, WPS for SAS language) is going to get a bigger chunk of new users and analysts.

Analytics skills are hot. There is big new demand for hot new skills by millions of unemployed Americans and Asians. How do you think this services market will play out?

If the US government could pump 800 Billion for bailouts, how much is your opinion it should spend on training programs to help citizens compete globally?

From http://www.nytimes.com/2010/10/03/business/economy/03skills.html?hpw

The national program is a response to frustrations from both workers and employers who complain that public retraining programs frequently do not provide students with employable skills. This new initiative is intended to help better align community college curriculums with the demands of local companies.

SAS recognizes the market –

see http://www.sas.com/news/preleases/aba-tech-engage.html

In tough economic times, it is more important than ever that companies be able to make better decisions using analytics. SAS is involved in two programs this summer that offer MBAs and unemployed technology workers the opportunity to learn and enhance analytics skills, and increase their marketability.

SAS is a partner in TechEngage, a week-long program of training classes that offer unemployed technology professionals new skills at a low cost to help them compete effectively in the marketplace.”

So does IBM-

http://www-03.ibm.com/press/us/en/pressrelease/28994.wss

. “Fordham has a long history of collaboration with IBM that has brought innovative new skills to our curriculum to prepare students for future jobs. With this effort, Fordham is preparing students with marketable skills for a coming wave of jobs in healthcare, sustainability, and social services where analytics can be applied to everyday challenges.”

and R

Well TIBCO and Revolution ….hmmm…mmmm

I am not sure there is even a R Analytics Certification program at the least.

Sub Prime Crisis: A Risk Analyst view from the Trenches

Pricing of Future Securities and Derivatives Based on Mortgage Assets are all about projecting delinquency rates , and it depends on the analysts to be either conservative in projecting a high rate or optimistic in a low rate.

Based on these projections , the assets are priced, packed up in SPV’s or collateralized, and options priced. Now Senior Management gets a big bonus if they sell off their balance sheet like this, and business is able to use cash generated to create higher loans….. so they lean on the analyst to Continue reading “Sub Prime Crisis: A Risk Analyst view from the Trenches”

Keeping them honest

A great example of a central bank using technology is Reserve Bank of India, whose banking ombudsman has an online form which is quite user friendly.

You can see the form here-

https://reservebank.org.in/BO/compltindex.htm

The form, which has very simple drop downs for segmenting, adequate linking to relevant policy for easy checklist of complaint.

So if your bank hid an extra line in the fine print , or deducted an extra emi as additional charges or just plain acted as in violation of Code of Conduct (there are 18 defined clauses), you can use this link to submit a complaint conveniently.

That Dude , Gandhi

At the end of 1947, as India’s Congress leaders sought to put the ghosts of colonialism and the torments of Partition with Pakistan behind them, a debate rose on economic policy. The first Prime Minister Jawahar Lal Nehru ,argued for and was successful in implementing a state led economic policy which focused on industrialization.

The alternatives were Free market capitalism , which was not in favor since it was less than 15 years to the ravages of the Depression and Gandhi’s philosophy of village led growth, including small co-operatives . India officially discarded the Nehruvian philosophy of socialism in the 1990’s with a step wise approach to free market reforms. Yet in today’s suddenly environmental conscious world of high oil prices,and debris of free market capitalism , it seems Gandhi’s economic policies of environmentally sustainable de centralized growth are as relevant as his political philosophy of non violence (an eye for an eye leads to a world of the blind).

If a 100 million Indian and Chinese cars bloomed tomorrow ,as some of the world’s industrialists would want, the smoke would cover the rest of the world.

That Dude, Gandhi was right. But he always was, wasn’t he.

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