Tag: websites

Why open source companies dont dance?

I have been pondering on this seemingly logical paradox for some time now-

1) Why are open source solutions considered technically better but not customer friendly.

2) Why do startups and app creators in social media or mobile get much more press coverage than

profitable startups in enterprise software.

3) How does tech journalism differ in covering open source projects in enterprise versus retail software.

4) What are the hidden rules of the game of enterprise software.

Some observations-

1) Open source companies often focus much more on technical community management and crowd sourcing code. Traditional software companies focus much more on managing the marketing community of customers and influencers. Accordingly the balance of power is skewed in favor of techies and R and D in open source companies, and in favor of marketing and analyst relations in traditional software companies.

Traditional companies also spend much more on hiring top notch press release/public relationship agencies, while open source companies are both financially and sometimes ideologically opposed to older methods of marketing software. The reverse of this is you are much more likely to see Videos and Tutorials by an open source company than a traditional company. You can compare the websites of Cloudera, DataStax, Hadapt ,Appistry and Mapr and contrast that with Teradata or Oracle (which has a much bigger and much more different marketing strategy.

Social media for marketing is also more efficiently utilized by smaller companies (open source) while bigger companies continue to pay influential analysts for expensive white papers that help present the brand.

Lack of budgets is a major factor that limits access to influential marketing for open source companies particularly in enterprise software.

2 and 3) Retail software is priced at 2-100$ and sells by volume. Accordingly technology coverage of these software is based on volume.

Enterprise software is much more expensively priced and has much more discreet volume or sales points. Accordingly the technology coverage of enterprise software is more discreet, in terms of a white paper coming every quarter, a webinar every month and a press release every week. Retail software is covered non stop , but these journalists typically do not charge for “briefings”.

Journalists covering retail software generally earn money by ads or hosting conferences. So they have an interest in covering new stuff or interesting disruptive stuff. Journalists or analysts covering enterprise software generally earn money by white papers, webinars, attending than hosting conferences, writing books. They thus have a much stronger economic incentive to cover existing landscape and technologies than smaller startups.

4) What are the hidden rules of the game of enterprise software.

  • It is mostly a white man’s world. this can be proved by statistical demographic analysis
  • There is incestuous intermingling between influencers, marketers, and PR people. This can be proved by simple social network analysis of who talks to who and how much. A simple time series between sponsorship and analysts coverage also will prove this (I am working on quantifying this ).
  • There are much larger switching costs to enterprise software than retail software. This leads to legacy shoddy software getting much chances than would have been allowed in an efficient marketplace.
  • Enterprise software is a less efficient marketplace than retail software in all definitions of the term “efficient markets”
  • Cloud computing, and SaaS and Open source threatens to disrupt the jobs and careers of a large number of people. In the long term, they will create many more jobs, but in the short term, people used to comfortable living of enterprise software (making,selling,or writing) will actively and passively resist these changes to the  paradigms in the current software status quo.
  • Open source companies dont dance and dont play ball. They prefer to hire 4 more college grads than commission 2 more white papers.

and the following with slight changes from a comment I made on a fellow blog-

  • While the paradigm on how to create new software has evolved from primarily silo-driven R and D departments to a broader collaborative effort, the biggest drawback is software marketing has not evolved.
  • If you want your own version of the open source community editions to be more popular, some standardization is necessary for the corporate decision makers, and we need better marketing paradigms.
  • While code creation is crowdsourced, solution implementation cannot be crowdsourced. Customers want solutions to a problem not code.
  • Just as open source as a production and licensing paradigm threatens to disrupt enterprise software, it will lead to newer ways to marketing software given the hostility of existing status quo.

 

 

#Rstats gets into Enterprise Cloud Software

Defense Agencies of the United States Departme...
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Here is an excellent example of how websites should help rather than hinder new customers take a demo of the software without being overwhelmed by sweet talking marketing guys who dont know the difference between heteroskedasticity, probability, odds and likelihood.

It is made by Zementis (Dr Michael Zeller has been a frequent guest here) and Revolution Analytics is still the best shot in Enterprise software for #Rstats

Now if only Revo could get into the lucrative Department of Energy or Department of Defense business- they could change the world AND earn some more revenue than they have been doing. But seriously.

Check out http://deployr.revolutionanalytics.com/zementis/ and play with it. or better still mash it with some data viz and ROC curves.- or extend it with some APIS 😉

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R for Analytics is now live

Okay, through the weekend I created a website for a few of my favourite things.

It’s on at https://rforanalytics.wordpress.com/

Graphical User Interfaces for R

 

Jerry Rubin said: “Don’t trust anyone over thirty

I dont trust anyone not using atleast one R GUI. Here’s a list of the top 10.

 

Code Enhancers for R

Here is a list of top 5 code enhancers,editors in R

R Commercial Software

A list of companies and software making (and) selling R software (and) services. Hint- it is almost 5 (unless I missed someone)

R Graphs Resources

R’s famous graphing capabilities and equally famous learning curve can be made a bit more humane- using some of these resources.

Internet Browsing

Because that’s what I do (all I do as per my cat) , and I am pretty good at it.

Using R from other Software

R can be used successfully from a lot of analytical software including some surprising ones praising the great 3000 packages library.

(to be continued- as I find more stuff I will keep it there, some ideas- database access from R, prominent R consultants, prominent R packages, famous R interviewees 😉 )

ps- The quote from Jerry Rubin seems funny for a while. I turn 34 this year.

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SAS Knowledge Exchange

Visual analytics : research and practice
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Here is an interesting website by SAS.com – it showcases lots of business analytics content more from a conceptual rather than a tool based perspective- have a glance yourself.

http://www.sas.com/knowledge-exchange/business-analytics/

Copyright © SAS Institute Inc. All rights reserved

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Computer Education grants from Google

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Image via CrunchBase

message from the official google blog-

http://googleblog.blogspot.com/2011/01/supporting-computer-science-education.html

With programs like Computer Science for High School (CS4HS), we hope to increase the number of CS majors —and therefore the number of people entering into careers in CS—by promoting computer science curriculum at the high school level.

For the fourth consecutive year, we’re funding CS4HS to invest in the next generation of computer scientists and engineers. CS4HS is a workshop for high school and middle school computer science teachers that introduces new and emerging concepts in computing and provides tips, tools and guidance on how to teach them. The ultimate goals are to “train the trainer,” develop a thriving community of high school CS teachers and spread the word about the awe and beauty of computing.

If you’re a university, community college, or technical School in the U.S., Canada, Europe, Middle East or Africa and are interested in hosting a workshop at your institution, please visit www.cs4hs.com to submit an application for grant funding.Applications will be accepted between January 18, 2011 and February 18, 2011.

In addition to submitting your application, on the CS4HS website you’ll find info on how to organize a workshop, as well as websites and agendas from last year’s participants to give you an idea of how the workshops were structured in the past. There’s also a collection ofCS4HS curriculum modules that previous participating schools have shared for future organizers to use in their own program.

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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.

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