Interview Luis Torgo Author Data Mining with R

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Here is an interview with Prof Luis Torgo, author of the recent best seller “Data Mining with R-learning with case studies”.

Ajay- Describe your career in science. How do you think can more young people be made interested in science.

Luis- My interest in science only started after I’ve finished my degree. I’ve entered a research lab at the University of Porto and started working on Machine Learning, around 1990. Since then I’ve been involved generally in data analysis topics both from a research perspective as well as from a more applied point of view through interactions with industry partners on several projects. I’ve spent most of my career at the Faculty of Economics of the University of Porto, but since 2008 I’m at the department of Computer Science of the Faculty of Sciences of the same university. At the same time I’ve been a researcher at LIAAD / Inesc Porto LA (www.liaad.up.pt).

I like a lot what I do and like science and the “scientific way of thinking”, but I cannot say that I’ve always thought of this area as my “place”. Most of all I like solving challenging problems through data analysis. If that translates into some scientific outcome than I’m more satisfied but that is not my main goal, though I’m kind of “forced” to think about that because of the constraints of an academic career.

That does not mean I’m not passionate about science, I just think there are many more ways of “doing science” than what is reflected in the usual “scientific indicators” that most institutions seem to be more and more obsessed about.

Regards interesting young people in science that is a hard question that I’m not sure I’m qualified to answer. I do tend to think that young people are more sensible to concrete examples of problems they think are interesting and that science helps in solving, as a way of finding a motivation for facing the hard work they will encounter in a scientific career. I do believe in case studies as a nice way to learn and motivate, and thus my book 😉

Ajay- Describe your new book “Data Mining with R, learning with case studies” Why did you choose a case study based approach? who is the target audience? What is your favorite case study from the book

Luis- This book is about learning how to use R for data mining. The book follows a “learn by doing it” approach to data mining instead of the more common theoretical description of the available techniques in this discipline. This is accomplished by presenting a series of illustrative case studies for which all necessary steps, code and data are provided to the reader. Moreover, the book has an associated web page (www.liaad.up.pt/~ltorgo/DataMiningWithR) where all code inside the book is given so that easy copy-paste is possible for the more lazy readers.

The language used in the book is very informal without many theoretical details on the used data mining techniques. For obtaining these theoretical insights there are already many good data mining books some of which are referred in “further readings” sections given throughout the book. The decision of following this writing style had to do with the intended target audience of the book.

In effect, the objective was to write a monograph that could be used as a supplemental book for practical classes on data mining that exist in several courses, but at the same time that could be attractive to professionals working on data mining in non-academic environments, and thus the choice of this more practically oriented approach.

Regards my favorite case study that is a hard question for an author… still I would probably choose the “Predicting Stock Market Returns” case study (Chapter 3). Not only because I like this challenging problem, but mainly because the case study addresses all aspects of knowledge discovery in a real world scenario and not only the construction of predictive models. It tackles data collection, data pre-processing, model construction, transforming predictions into actions using different trading policies, using business-related performance metrics, implementing a trading simulator for “real-world” evaluation, and laying out grounds for constructing an online trading system.

Obviously, for all these steps there are far too many options to be possible to describe/evaluate all of them in a chapter, still I do believe that for the reader it is important to see the overall picture, and read about the relevant questions on this problem and some possible paths that can be followed at these different steps.

In other words: do not expect to become rich with the solution I describe in the chapter !

Ajay- Apart from R, what other data mining software do you use or have used in the past. How would you compare their advantages and disadvantages with R

Luis- I’ve played around with Clementine, Weka, RapidMiner and Knime, but really only playing with teaching goals, and no serious use/evaluation in the context of data mining projects. For the latter I mainly use R or software developed by myself (either in R or other languages). In this context, I do not think it is fair to compare R with these or other tools as I lack serious experience with them. I can however, tell you about what I see as the main pros and cons of R. The main reason for using R is really not only the power of the tool that does not stop surprising me in terms of what already exists and keeps appearing as contributions of an ever growing community, but mainly the ability of rapidly transforming ideas into prototypes. Regards some of its drawbacks I would probably mention the lack of efficiency when compared to other alternatives and the problem of data set sizes being limited by main memory.

I know that there are several efforts around for solving this latter issue not only from the community (e.g. http://cran.at.r-project.org/web/views/HighPerformanceComputing.html), but also from the industry (e.g. Revolution Analytics), but I would prefer that at this stage this would be a standard feature of the language so the the “normal” user need not worry about it. But then this is a community effort and if I’m not happy with the current status instead of complaining I should do something about it!

Ajay- Describe your writing habit- How do you set about writing the book- did you write a fixed amount daily or do you write in bursts etc

Luis- Unfortunately, I write in bursts whenever I find some time for it. This is much more tiring and time consuming as I need to read back material far too often, but I cannot afford dedicating too much consecutive time to a single task. Actually, I frequently tease my PhD students when they “complain” about the lack of time for doing what they have to, that they should learn to appreciate the luxury of having a single task to complete because it will probably be the last time in their professional life!

Ajay- What do you do to relax or unwind when not working?

Luis- For me, the best way to relax from work is by playing sports. When I’m involved in some game I reset my mind and forget about all other things and this is very relaxing for me. A part from sports I enjoy a lot spending time with my family and friends. A good and long dinner with friends over a good bottle of wine can do miracles when I’m too stressed with work! Finally,I do love traveling around with my family.

Luis Torgo

Short Bio: Luis Torgo has a degree in Systems and Informatics Engineering and a PhD in Computer Science. He is an Associate Professor of the Department of Computer Science of the Faculty of Sciences of the University of Porto. He is also a researcher of the Laboratory of Artificial Intelligence and Data Analysis (LIAAD) belonging to INESC Porto LA. Luis Torgo has been an active researcher in Machine Learning and Data Mining for more than 20 years. He has lead several academic and industrial Data Mining research projects. Luis Torgo accompanies the R project almost since its beginning, using it on his research activities. He teaches R at different levels and has given several courses in different countries.

For reading “Data Mining with R” – you can visit this site, also to avail of a 20% discount the publishers have generously given (message below)-

For more information and to place an order, visit us at http://www.crcpress.com.  Order online and apply 20% Off discount code 907HM at checkout.  CRC is pleased to offer free standard shipping on all online orders!

link to the book page  http://www.crcpress.com/product/isbn/9781439810187

Price: $79.95
Cat. #: K10510
ISBN: 9781439810187
ISBN 10: 1439810184
Publication Date: November 09, 2010
Number of Pages: 305
Availability: In Stock
Binding(s): Hardback 

PAW Videos

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Predictive Analytics World March 2011 in San Francisco

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Predictive Analytics World is pleased to announce on-demand access to the videos of PAW Washington DC, October 2010, including over 30 sessions and keynotes that you may view at your convenience. Access this leading predictive analytics content online now:

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Session Gallery: Day 1 of 2

Viewing (17) Sessions of (31)

 

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Keynote: Five Ways Predictive Analytics Cuts Enterprise Risk  

Eric Siegel, Ph.D., Program Chair, Predictive Analytics World

All business is an exercise in risk management. All organizations would benefit from measuring, tracking and computing risk as a core process, much like insurance companies do.

Predictive analytics does the trick, one customer at a time. This technology is a data-driven means to compute the risk each customer will defect, not respond to an expensive mailer, consume a retention discount even if she were not going to leave in the first place, not be targeted for a telephone solicitation that would have landed a sale, commit fraud, or become a “loss customer” such as a bad debtor or an insurance policy-holder with high claims.

In this keynote session, Dr. Eric Siegel reveals:

– Five ways predictive analytics evolves your enterprise to reduce risk

– Hidden sources of risk across operational functions

– What every business should learn from insurance companies

– How advancements have reversed the very meaning of fraud

– Why “man + machine” teams are greater than the sum of their parts for enterprise decision support

Length – 00:45:57 | Email to a Colleague

Price: $195

 

 

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Play video of session: Platinum Sponsor Presentation, Analytics: The Beauty of Diversity
Platinum Sponsor Presentation: Analytics – The Beauty of Diversity 

Anne H. Milley, Senior Director of Analytic Strategy, Worldwide Product Marketing, SAS

Analytics contributes to, and draws from, multiple disciplines. The unifying theme of “making the world a better place” is bred from diversity. For instance, the same methods used in econometrics might be used in market research, psychometrics and other disciplines. In a similar way, diverse paradigms are needed to best solve problems, reveal opportunities and make better decisions. This is why we evolve capabilities to formulate and solve a wide range of problems through multiple integrated languages and interfaces. Extending that, we have provided integration with other languages so that users can draw on the disciplines and paradigms needed to best practice their craft.

Length – 20:11 | Email to a Colleague

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Play video of session: Gold Sponsor Presentation Predictive Analytics Accelerate Insight for Financial Services
Gold Sponsor Presentation: Predictive Analytics Accelerate Insight for Financial Services 

Finbarr Deely, Director of Business Development,ParAccel

Financial services organizations face immense hurdles in maintaining profitability and building competitive advantage. Financial services organizations must perform “what-if” scenario analysis, identify risks, and detect fraud patterns. The advanced analytic complexity required often makes such analysis slow and painful, if not impossible. This presentation outlines the analytic challenges facing these organizations and provides a clear path to providing the accelerated insight needed to perform in today’s complex business environment to reduce risk, stop fraud and increase profits. * The value of predictive analytics in Accelerating Insight * Financial Services Analytic Case Studies * Brief Overview of ParAccel Analytic Database

Length – 09:06 | Email to a Colleague

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TOPIC: BUSINESS VALUE
Case Study: Monster.com
Creating Global Competitive Power with Predictive Analytics 

Jean Paul Isson, Vice President, Globab BI & Predictive Analytics, Monster Worldwide

Using Predictive analytics to gain a deeper understanding of customer behaviours, increase marketing ROI and drive growth

– Creating global competitive power with business intelligence: Making the right decisions – at the right time

– Avoiding common change management challenges in sales, marketing, customer service, and products

– Developing a BI vision – and implementing it: successful business intelligence implementation models

– Using predictive analytics as a business driver to stay on top of the competition

– Following the Monster Worldwide global BI evolution: How Monster used BI to go from good to great

Length – 51:17 | Email to a Colleague

Price: $195

 

 

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TOPIC: SURVEY ANALYSIS
Case Study: YMCA
Turning Member Satisfaction Surveys into an Actionable Narrative 

Dean Abbott, President, Abbott Analytics

Employees are a key constituency at the Y and previous analysis has shown that their attitudes have a direct bearing on Member Satisfaction. This session will describe a successful approach for the analysis of YMCA employee surveys. Decision trees are built and examined in depth to identify key questions in describing key employee satisfaction metrics, including several interesting groupings of employee attitudes. Our approach will be contrasted with other factor analysis and regression-based approaches to survey analysis that we used initially. The predictive models described are currently in use and resulted in both greater understanding of employee attitudes, and a revised “short-form” survey with fewer key questions identified by the decision trees as the most important predictors.

Length – 50:19 | Email to a Colleague

Price: $195

 

 

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TOPIC: INDUSTRY TRENDS
2010 Data Minter Survey Results: Highlights
 

Karl Rexer, Ph.D., Rexer Analytics

Do you want to know the views, actions, and opinions of the data mining community? Each year, Rexer Analytics conducts a global survey of data miners to find out. This year at PAW we unveil the results of our 4th Annual Data Miner Survey. This session will present the research highlights, such as:

– Analytic goals & key challenges

– Impact of the economy

– Regional differences

– Text mining trends

Length – 15:20 | Email to a Colleague

Price: $195

 

 

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Multiple Case Studies: U.S. DoD, U.S. DHS, SSA
Text Mining: Lessons Learned 

John F. Elder, Chief Scientist, Elder Research, Inc.

Text Mining is the “Wild West” of data mining and predictive analytics – the potential for gain is huge, the capability claims are often tall tales, and the “land rush” for leadership is very much a race.

In solving unstructured (text) analysis challenges, we found that principles from inductive modeling – learning relationships from labeled cases – has great power to enhance text mining. Dr. Elder highlights key technical breakthroughs discovered while working on projects for leading government agencies, including: Text Mining is the “Wild West” of data mining and predictive analytics – the potential for gain is huge, the capability claims are often tall tales, and the “land rush” for leadership is very much a race.

– Prioritizing searches for the Dept. of Homeland Security

– Quick decisions for Social Security Admin. disability

– Document discovery for the Dept. of Defense

– Disease discovery for the Dept. of Homeland Security

– Risk profiling for the Dept. of Defense

Length – 48:58 | Email to a Colleague

Price: $195

 

 

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Play video of session: Keynote: How Target Gets the Most out of Its Guest Data to Improve Marketing ROI
Keynote: How Target Gets the Most out of Its Guest Data to Improve Marketing ROI 

Andrew Pole, Senior Manager, Media and Database Marketing, Target

In this session, you’ll learn how Target leverages its own internal guest data to optimize its direct marketing – with the ultimate goal of enhancing our guests’ shopping experience and driving in-store and online performance. You will hear about what guest data is available at Target, how and where we collect it, and how it is used to improve the performance and relevance of direct marketing vehicles. Furthermore, we will discuss Target’s development and usage of guest segmentation, response modeling, and optimization as means to suppress poor performers from mailings, determine relevant product categories and services for online targeted content, and optimally assign receipt marketing offers to our guests when offer quantities are limited.

Length – 47:49 | Email to a Colleague

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Play video of session: Platinum Sponsor Presentation: Driving Analytics Into Decision Making
Platinum Sponsor Presentation: Driving Analytics Into Decision Making  

Jason Verlen, Director, SPSS Product Strategy & Management, IBM Software Group

Organizations looking to dramatically improve their business outcomes are turning to decision management, a convergence of technology and business processes that is used to streamline and predict the outcome of daily decision-making. IBM SPSS Decision Management technology provides the critical link between analytical insight and recommended actions. In this session you’ll learn how Decision Management software integrates analytics with business rules and business applications for front-line systems such as call center applications, insurance claim processing, and websites. See how you can improve every customer interaction, minimize operational risk, reduce fraud and optimize results.

Length – 17:29 | Email to a Colleague

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TOPIC: DATA INFRASTRUCTURE AND INTEGRATION
Case Study: Macy’s
The world is not flat (even though modeling software has to think it is) 

Paul Coleman, Director of Marketing Statistics, Macy’s Inc.

Software for statistical modeling generally use flat files, where each record represents a unique case with all its variables. In contrast most large databases are relational, where data are distributed among various normalized tables for efficient storage. Variable creation and model scoring engines are necessary to bridge data mining and storage needs. Development datasets taken from a sampled history require snapshot management. Scoring datasets are taken from the present timeframe and the entire available universe. Organizations, with significant data, must decide when to store or calculate necessary data and understand the consequences for their modeling program.

Length – 34:54 | Email to a Colleague

Price: $195

 

 

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TOPIC: CUSTOMER VALUE
Case Study: SunTrust
When One Model Will Not Solve the Problem – Using Multiple Models to Create One Solution 

Dudley Gwaltney, Group Vice President, Analytical Modeling, SunTrust Bank

In 2007, SunTrust Bank developed a series of models to identify clients likely to have large changes in deposit balances. The models include three basic binary and two linear regression models.

Based on the models, 15% of SunTrust clients were targeted as those most likely to have large balance changes. These clients accounted for 65% of the absolute balance change and 60% of the large balance change clients. The targeted clients are grouped into a portfolio and assigned to individual SunTrust Retail Branch. Since 2008, the portfolio generated a 2.6% increase in balances over control.

Using the SunTrust example, this presentation will focus on:

– Identifying situations requiring multiple models

– Determining what types of models are needed

– Combining the individual component models into one output

Length – 48:22 | Email to a Colleague

Price: $195

 

 

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TOPIC: RESPONSE & CROSS-SELL
Case Study: Paychex
Staying One Step Ahead of the Competition – Development of a Predictive 401(k) Marketing and Sales Campaign 

Jason Fox, Information Systems and Portfolio Manager,Paychex

In-depth case study of Paychex, Inc. utilizing predictive modeling to turn the tides on competitive pressures within their own client base. Paychex, a leading provider of payroll and human resource solutions, will guide you through the development of a Predictive 401(k) Marketing and Sales model. Through the use of sophisticated data mining techniques and regression analysis the model derives the probability a client will add retirement services products with Paychex or with a competitor. Session will include roadblocks that could have ended development and ROI analysis. Speaker: Frank Fiorille, Director of Enterprise Risk Management, Paychex Speaker: Jason Fox, Risk Management Analyst, Paychex

Length – 26:29 | Email to a Colleague

Price: $195

 

 

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TOPIC: SEGMENTATION
Practitioner: Canadian Imperial Bank of Commerce
Segmentation Do’s and Don’ts 

Daymond Ling, Senior Director, Modelling & Analytics,Canadian Imperial Bank of Commerce

The concept of Segmentation is well accepted in business and has withstood the test of time. Even with the advent of new artificial intelligence and machine learning methods, this old war horse still has its place and is alive and well. Like all analytical methods, when used correctly it can lead to enhanced market positioning and competitive advantage, while improper application can have severe negative consequences.

This session will explore what are the elements of success, and what are the worse practices that lead to failure. The relationship between segmentation and predictive modeling will also be discussed to clarify when it is appropriate to use one versus the other, and how to use them together synergistically.

Length – 45:57 | Email to a Colleague

Price: $195

 

 

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TOPIC: SOCIAL DATA
Thought Leadership
Social Network Analysis: Killer Application for Cloud Analytics
 

James Kobielus, Senior Analyst, Forrester Research

Social networks such as Twitter and Facebook are a potential goldmine of insights on what is truly going through customers´minds. Every company wants to know whether, how, how often, and by whom they´re being mentioned across the billowing new cloud of social media. Just as important, every company wants to influence those discussions in their favor, target new business, and harvest maximum revenue potential. In this session, Forrester analyst James Kobielus identifies fruitful applications of social network analysis in customer service, sales, marketing, and brand management. He presents a roadmap for enterprises to leverage their inline analytics initiatives and leverage high-performance data warehousing (DW) clouds and appliances in order to analyze shifting patterns of customer sentiment, influence, and propensity. Leveraging Forrester’s ongoing research in advanced analytics and customer relationship management, Kobielus will discuss industry trends, commercial modeling tools, and emerging best practices in social network analysis, which represents a game-changing new discipline in predictive analytics.

Length – 48:16 | Email to a Colleague

Price: $195

 

 

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TOPIC: HEALTHCARE – INTERNATIONAL TARGETING
Case Study: Life Line Screening
Taking CRM Global Through Predictive Analytics 

Ozgur Dogan,
VP, Quantitative Solutions Group, Merkle Inc

Trish Mathe,
Director of Database Marketing, Life Line Screening

While Life Line is successfully executing a US CRM roadmap, they are also beginning this same evolution abroad. They are beginning in the UK where Merkle procured data and built a response model that is pulling responses over 30% higher than competitors. This presentation will give an overview of the US CRM roadmap, and then focus on the beginning of their strategy abroad, focusing on the data procurement they could not get anywhere else but through Merkle and the successful modeling and analytics for the UK. Speaker: Ozgur Dogan, VP, Quantitative Solutions Group, Merkle Inc Speaker: Trish Mathe, Director of Database Marketing, Life Line Screening

Length – 40:12 | Email to a Colleague

Price: $195

 

 

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TOPIC: SURVEY ANALYSIS
Case Study: Forrester
Making Survey Insights Addressable and Scalable – The Case Study of Forrester’s Technographics Benchmark Survey 

Nethra Sambamoorthi, Team Leader, Consumer Dynamics & Analytics, Global Consulting, Acxiom Corporation

Marketers use surveys to create enterprise wide applicable strategic insights to: (1) develop segmentation schemes, (2) summarize consumer behaviors and attitudes for the whole US population, and (3) use multiple surveys to draw unified views about their target audience. However, these insights are not directly addressable and scalable to the whole consumer universe which is very important when applying the power of survey intelligence to the one to one consumer marketing problems marketers routinely face. Acxiom partnered with Forrester Research, creating addressable and scalable applications of Forrester’s Technographics Survey and applied it successfully to a number of industries and applications.

Length – 39:23 | Email to a Colleague

Price: $195

 

 

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TOPIC: HEALTHCARE
Case Study: UPMC Health Plan
A Predictive Model for Hospital Readmissions 

Scott Zasadil, Senior Scientist, UPMC Health Plan

Hospital readmissions are a significant component of our nation’s healthcare costs. Predicting who is likely to be readmitted is a challenging problem. Using a set of 123,951 hospital discharges spanning nearly three years, we developed a model that predicts an individual’s 30-day readmission should they incur a hospital admission. The model uses an ensemble of boosted decision trees and prior medical claims and captures 64% of all 30-day readmits with a true positive rate of over 27%. Moreover, many of the ‘false’ positives are simply delayed true positives. 53% of the predicted 30-day readmissions are readmitted within 180 days.

Length – 54:18 | Email to a Colleague

Price: $195

How to balance your online advertising and your offline conscience

Google in 1998, showing the original logo
Image via Wikipedia

I recently found an interesting example of  a website that both makes a lot of money and yet is much more efficient than any free or non profit. It is called ECOSIA

If you see a website that wants to balance administrative costs  plus have a transparent way to make the world better- this is a great example.

  • http://ecosia.org/how.php
  • HOW IT WORKS
    You search with Ecosia.
  • Perhaps you click on an interesting sponsored link.
  • The sponsoring company pays Bing or Yahoo for the click.
  • Bing or Yahoo gives the bigger chunk of that money to Ecosia.
  • Ecosia donates at least 80% of this income to support WWF’s work in the Amazon.
  • If you like what we’re doing, help us spread the word!
  • Key facts about the park:

    • World’s largest tropical forest reserve (38,867 square kilometers, or about the size of Switzerland)
    • Home to about 14% of all amphibian species and roughly 54% of all bird species in the Amazon – not to mention large populations of at least eight threatened species, including the jaguar
    • Includes part of the Guiana Shield containing 25% of world’s remaining tropical rainforests – 80 to 90% of which are still pristine
    • Holds the last major unpolluted water reserves in the Neotropics, containing approximately 20% of all of the Earth’s water
    • One of the last tropical regions on Earth vastly unaltered by humans
    • Significant contributor to climatic regulation via heat absorption and carbon storage

     

    http://ecosia.org/statistics.php

    They claim to have donated 141,529.42 EUR !!!

    http://static.ecosia.org/files/donations.pdf

     

     

     

     

     

     

     

     

     

     

    Well suppose you are the Web Admin of a very popular website like Wikipedia or etc

    One way to meet server costs is to say openly hey i need to balance my costs so i need some money.

    The other way is to use online advertising.

    I started mine with Google Adsense.

    Click per milli (or CPM)  gives you a very low low conversion compared to contacting ad sponsor directly.

    But its a great data experiment-

    as you can monitor which companies are likely to be advertised on your site (assume google knows more about their algols than you will)

    which formats -banner or text or flash have what kind of conversion rates

    what are the expected pay off rates from various keywords or companies (like business intelligence software, predictive analytics software and statistical computing software are similar but have different expected returns (if you remember your eco class)

     

    NOW- Based on above data, you know whats your minimum baseline to expect from a private advertiser than a public, crowd sourced search engine one (like Google or Bing)

    Lets say if you have 100000 views monthly. and assume one out of 1000 page views will lead to a click. Say the advertiser will pay you 1 $ for every 1 click (=1000 impressions)

    Then your expected revenue is $100.But if your clicks are priced at 2.5$ for every click , and your click through rate is now 3 out of 1000 impressions- (both very moderate increases that can done by basic placement optimization of ad type, graphics etc)-your new revenue is  750$.

    Be a good Samaritan- you decide to share some of this with your audience -like 4 Amazon books per month ( or I free Amazon book per week)- That gives you a cost of 200$, and leaves you with some 550$.

    Wait! it doesnt end there- Adam Smith‘s invisible hand moves on .

    You say hmm let me put 100 $ for an annual paper writing contest of $1000, donate $200 to one laptop per child ( or to Amazon rain forests or to Haiti etc etc etc), pay $100 to your upgraded server hosting, and put 350$ in online advertising. say $200 for search engines and $150 for Facebook.

    Woah!

    Month 1 would should see more people  visiting you for the first time. If you have a good return rate (returning visitors as a %, and low bounce rate (visits less than 5 secs)- your traffic should see atleast a 20% jump in new arrivals and 5-10 % in long term arrivals. Ignoring bounces- within  three months you will have one of the following

    1) An interesting case study on statistics on online and social media advertising, tangible motivations for increasing community response , and some good data for study

    2) hopefully better cost management of your server expenses

    3)very hopefully a positive cash flow

     

    you could even set a percentage and share the monthly (or annually is better actions) to your readers and advertisers.

    go ahead- change the world!

    the key paradigms here are sharing your traffic and revenue openly to everyone

    donating to a suitable cause

    helping increase awareness of the suitable cause

    basing fixed percentages rather than absolute numbers to ensure your site and cause are sustained for years.

    R Journal Dec 2010 and R for Business Analytics

    A Bold GNU Head
    Image via Wikipedia

    I almost missed out on the R Journal for this month- great reading,

    and I liked Dr Hadley’s article on stringr package the best. Really really useful package and nice writing too

    http://journal.r-project.org/archive/2010-2/RJournal_2010-2_Wickham.pdf

    (incidentally I just downloaded a local copy of his ggplot website at http://had.co.nz/ggplot2/ggplot-static.zip

    I aim to really read that one up

    Okay, announcement time

    I just signed a contract with Springer for a book on R, some what in first half of 2011

    ” R for Business Analytics

    its going to be a more business analytics than a stats perspective ( I am a MBA /Mech Engineer)

    and use cases would be business analytics cases. Do write to me if you need help doing some analytics in R (business use cases)- or want something featured. Big focus would be on GUI and easier analytics, using the Einsteinian principle to make things as simple as possible but no simpler)

    PAWCON -This week in London

    Watch out for the twitter hash news on PAWCON and the exciting agenda lined up. If your in the City- you may want to just drop in

    http://www.predictiveanalyticsworld.com/london/2010/agenda.php#day1-7

    Disclaimer- PAWCON has been a blog partner with Decisionstats (since the first PAWCON ). It is vendor neutral and features open source as well proprietary software, as well case studies from academia and Industry for a balanced view.

     

    Little birdie told me some exciting product enhancements may be in the works including a not yet announced R plugin 😉 and the latest SAS product using embedded analytics and Dr Elder’s full day data mining workshop.

    Citation-

    http://www.predictiveanalyticsworld.com/london/2010/agenda.php#day1-7

    Monday November 15, 2010
    All conference sessions take place in Edward 5-7

    8:00am-9:00am

    Registration, Coffee and Danish
    Room: Albert Suites


    9:00am-9:50am

    Keynote
    Five Ways Predictive Analytics Cuts Enterprise Risk

    All business is an exercise in risk management. All organizations would benefit from measuring, tracking and computing risk as a core process, much like insurance companies do.

    Predictive analytics does the trick, one customer at a time. This technology is a data-driven means to compute the risk each customer will defect, not respond to an expensive mailer, consume a retention discount even if she were not going to leave in the first place, not be targeted for a telephone solicitation that would have landed a sale, commit fraud, or become a “loss customer” such as a bad debtor or an insurance policy-holder with high claims.

    In this keynote session, Dr. Eric Siegel will reveal:

    • Five ways predictive analytics evolves your enterprise to reduce risk
    • Hidden sources of risk across operational functions
    • What every business should learn from insurance companies
    • How advancements have reversed the very meaning of fraud
    • Why “man + machine” teams are greater than the sum of their parts for
    • enterprise decision support

     

    Speaker: Eric Siegel, Ph.D., Program Chair, Predictive Analytics World

    Top of this page ] [ Agenda overview ]


    IBM9:50am-10:10am

    Platinum Sponsor Presentation
    The Analytical Revolution

    The algorithms at the heart of predictive analytics have been around for years – in some cases for decades. But now, as we see predictive analytics move to the mainstream and become a competitive necessity for organisations in all industries, the most crucial challenges are to ensure that results can be delivered to where they can make a direct impact on outcomes and business performance, and that the application of analytics can be scaled to the most demanding enterprise requirements.

    This session will look at the obstacles to successfully applying analysis at the enterprise level, and how today’s approaches and technologies can enable the true “industrialisation” of predictive analytics.

    Speaker: Colin Shearer, WW Industry Solutions Leader, IBM UK Ltd

    Top of this page ] [ Agenda overview ]


    Deloitte10:10am-10:20am

    Gold Sponsor Presentation
    How Predictive Analytics is Driving Business Value

    Organisations are increasingly relying on analytics to make key business decisions. Today, technology advances and the increasing need to realise competitive advantage in the market place are driving predictive analytics from the domain of marketers and tactical one-off exercises to the point where analytics are being embedded within core business processes.

    During this session, Richard will share some of the focus areas where Deloitte is driving business transformation through predictive analytics, including Workforce, Brand Equity and Reputational Risk, Customer Insight and Network Analytics.

    Speaker: Richard Fayers, Senior Manager, Deloitte Analytical Insight

    Top of this page ] [ Agenda overview ]


    10:20am-10:45am

    Break / Exhibits
    Room: Albert Suites


    10:45am-11:35am
    Healthcare
    Case Study: Life Line Screening
    Taking CRM Global Through Predictive Analytics

    While Life Line is successfully executing a US CRM roadmap, they are also beginning this same evolution abroad. They are beginning in the UK where Merkle procured data and built a response model that is pulling responses over 30% higher than competitors. This presentation will give an overview of the US CRM roadmap, and then focus on the beginning of their strategy abroad, focusing on the data procurement they could not get anywhere else but through Merkle and the successful modeling and analytics for the UK.

    Speaker: Ozgur Dogan, VP, Quantitative Solutions Group, Merkle Inc.

    Speaker: Trish Mathe, Life Line Screening

    Top of this page ] [ Agenda overview ]


    11:35am-12:25pm
    Open Source Analytics; Healthcare
    Case Study: A large health care organization
    The Rise of Open Source Analytics: Lowering Costs While Improving Patient Care

    Rapidminer and R were the number 1 and 2 in this years annual KDNuggets data mining tool usage poll, followed by Knime on place 4 and Weka on place 6. So what’s going on here? Are these open source tools really that good or is their popularity strongly correlated with lower acquisition costs alone? This session answers these questions based on a real world case for a large health care organization and explains the risks & benefits of using open source technology. The final part of the session explains how these tools stack up against their traditional, proprietary counterparts.

    Speaker: Jos van Dongen, Associate & Principal, DeltIQ Group

    Top of this page ] [ Agenda overview ]


    12:25pm-1:25pm

    Lunch / Exhibits
    Room: Albert Suites


    1:25pm-2:15pm
    Keynote
    Thought Leader:
    Case Study: Yahoo! and other large on-line e-businesses
    Search Marketing and Predictive Analytics: SEM, SEO and On-line Marketing Case Studies

    Search Engine Marketing is a $15B industry in the U.S. growing to double that number over the next 3 years. Worldwide the SEM market was over $50B in 2010. Not only is this a fast growing area of marketing, but it is one that has significant implications for brand and direct marketing and is undergoing rapid change with emerging channels such as mobile and social. What is unique about this area of marketing is a singularly heavy dependence on analytics:

     

    • Large numbers of variables and options
    • Real-time auctions/bids and a need to adjust strategies in real-time
    • Difficult optimization problems on allocating spend across a huge number of keywords
    • Fast-changing competitive terrain and heavy competition on the obvious channels
    • Complicated interactions between various channels and a large choice of search keyword expansion possibilities
    • Profitability and ROI analysis that are complex and often challenging

     

    The size of the industry, its growing importance in marketing, its upcoming role in Mobile Advertising, and its uniquely heavy reliance on analytics makes it particularly interesting as an area for predictive analytics applications. In this session, not only will hear about some of the latest strategies and techniques to optimize search, you will hear case studies that illustrate the important role of analytics from industry practitioners.

    Speaker: Usama Fayyad, , Ph.D., CEO, Open Insights

    Top of this page ] [ Agenda overview ]


    SAS2:15pm-2:35pm

    Platinum Sponsor Presentation
    Creating a Model Factory Using in-Database Analytics

    With the ever-increasing number of analytical models required to make fact-based decisions, as well as increasing audit compliance regulations, it is more important than ever that these models can be created, monitored, retuned and deployed as quickly and automatically as possible. This paper, using a case study from a major financial organisation, will show how organisations can build a model factory efficiently using the latest SAS technology that utilizes the power of in-database processing.

    Speaker: John Spooner, Analytics Specialist, SAS (UK)

    Top of this page ] [ Agenda overview ]


    2:35pm-2:45pm

    Session Break
    Room: Albert Suites


    2:45pm-3:35pm

    Retail
    Case Study: SABMiller
    Predictive Analytics & Global Marketing Strategy

    Over the last few years SABMiller plc, the second largest brewing company in the world operating in 70 countries, has been systematically segmenting its markets in different countries globally in order optimize their portfolio strategy & align it to their long term country specific growth strategy. This presentation talks about the overall methodology followed and the challenges that had to be overcome both from a technical as well as from a change management stand point in order to successfully implement a standard analytics approach to diverse markets and diverse business positions in a highly global setting.

    The session explains how country specific growth strategies were converted to objective variables and consumption occasion segments were created that differentiated the market effectively by their growth potential. In addition to this the presentation will also provide a discussion on issues like:

    • The dilemmas of static vs. dynamic solutions and standardization vs. adaptable solutions
    • Challenges in acceptability, local capability development, overcoming implementation inertia, cost effectiveness, etc
    • The role that business partners at SAB and analytics service partners at AbsolutData together play in providing impactful and actionable solutions

     

    Speaker: Anne Stephens, SABMiller plc

    Speaker: Titir Pal, AbsolutData

    Top of this page ] [ Agenda overview ]


    3:35pm-4:25pm

    Retail
    Case Study: Overtoom Belgium
    Increasing Marketing Relevance Through Personalized Targeting

     

    Since many years, Overtoom Belgium – a leading B2B retailer and division of the French Manutan group – focuses on an extensive use of CRM. In this presentation, we demonstrate how Overtoom has integrated Predictive Analytics to optimize customer relationships. In this process, they employ analytics to develop answers to the key question: “which product should we offer to which customer via which channel”. We show how Overtoom gained a 10% revenue increase by replacing the existing segmentation scheme with accurate predictive response models. Additionally, we illustrate how Overtoom succeeds to deliver more relevant communications by offering personalized promotional content to every single customer, and how these personalized offers positively impact Overtoom’s conversion rates.

    Speaker: Dr. Geert Verstraeten, Python Predictions

    Top of this page ] [ Agenda overview ]


    4:25pm-4:50pm

    Break / Exhibits
    Room: Albert Suites


    4:50pm-5:40pm
    Uplift Modelling:
    Case Study: Lloyds TSB General Insurance & US Bank
    Uplift Modelling: You Should Not Only Measure But Model Incremental Response

    Most marketing analysts understand that measuring the impact of a marketing campaign requires a valid control group so that uplift (incremental response) can be reported. However, it is much less widely understood that the targeting models used almost everywhere do not attempt to optimize that incremental measure. That requires an uplift model.

    This session will explain why a switch to uplift modelling is needed, illustrate what can and does go wrong when they are not used and the hugely positive impact they can have when used effectively. It will also discuss a range of approaches to building and assessing uplift models, from simple basic adjustments to existing modelling processes through to full-blown uplift modelling.

    The talk will use Lloyds TSB General Insurance & US Bank as a case study and also illustrate real-world results from other companies and sectors.

     

    Speaker: Nicholas Radcliffe, Founder and Director, Stochastic Solutions

    Top of this page ] [ Agenda overview ]


    5:40pm-6:30pm

    Consumer services
    Case Study: Canadian Automobile Association and other B2C examples
    The Diminishing Marginal Returns of Variable Creation in Predictive Analytics Solutions

     

    Variable Creation is the key to success in any predictive analytics exercise. Many different approaches are adopted during this process, yet there are diminishing marginal returns as the number of variables increase. Our organization conducted a case study on four existing clients to explore this so-called diminishing impact of variable creation on predictive analytics solutions. Existing predictive analytics solutions were built using our traditional variable creation process. Yet, presuming that we could exponentially increase the number of variables, we wanted to determine if this added significant benefit to the existing solution.

    Speaker: Richard Boire, BoireFillerGroup

    Top of this page ] [ Agenda overview ]


    6:30pm-7:30pm

    Reception / Exhibits
    Room: Albert Suites


    Tuesday November 16, 2010
    All conference sessions take place in Edward 5-7

    8:00am-9:00am

    Registration, Coffee and Danish
    Room: Albert Suites


    9:00am-9:55am
    Keynote
    Multiple Case Studies: Anheuser-Busch, Disney, HP, HSBC, Pfizer, and others
    The High ROI of Data Mining for Innovative Organizations

    Data mining and advanced analytics can enhance your bottom line in three basic ways, by 1) streamlining a process, 2) eliminating the bad, or 3) highlighting the good. In rare situations, a fourth way – creating something new – is possible. But modern organizations are so effective at their core tasks that data mining usually results in an iterative, rather than transformative, improvement. Still, the impact can be dramatic.

    Dr. Elder will share the story (problem, solution, and effect) of nine projects conducted over the last decade for some of America’s most innovative agencies and corporations:

      Streamline:

    • Cross-selling for HSBC
    • Image recognition for Anheuser-Busch
    • Biometric identification for Lumidigm (for Disney)
    • Optimal decisioning for Peregrine Systems (now part of Hewlett-Packard)
    • Quick decisions for the Social Security Administration
      Eliminate Bad:

    • Tax fraud detection for the IRS
    • Warranty Fraud detection for Hewlett-Packard
      Highlight Good:

    • Sector trading for WestWind Foundation
    • Drug efficacy discovery for Pharmacia & UpJohn (now Pfizer)

    Moderator: Eric Siegel, Program Chair, Predictive Analytics World

    Speaker: John Elder, Ph.D., Elder Research, Inc.

    Also see Dr. Elder’s full-day workshop

     

    Top of this page ] [ Agenda overview ]


    9:55am-10:30am

    Break / Exhibits
    Room: Albert Suites


    10:30am-11:20am
    Telecommunications
    Case Study: Leading Telecommunications Operator
    Predictive Analytics and Efficient Fact-based Marketing

    The presentation describes what are the major topics and issues when you introduce predictive analytics and how to build a Fact-Based marketing environment. The introduced tools and methodologies proved to be highly efficient in terms of improving the overall direct marketing activity and customer contact operations for the involved companies. Generally, the introduced approaches have great potential for organizations with large customer bases like Mobile Operators, Internet Giants, Media Companies, or Retail Chains.

    Main Introduced Solutions:-Automated Serial Production of Predictive Models for Campaign Targeting-Automated Campaign Measurements and Tracking Solutions-Precise Product Added Value Evaluation.

    Speaker: Tamer Keshi, Ph.D., Long-term contractor, T-Mobile

    Speaker: Beata Kovacs, International Head of CRM Solutions, Deutsche Telekom

    Top of this page ] [ Agenda overview ]


    11:20am-11:25am

    Session Changeover


    11:25am-12:15pm
    Thought Leader
    Nine Laws of Data Mining

    Data mining is the predictive core of predictive analytics, a business process that finds useful patterns in data through the use of business knowledge. The industry standard CRISP-DM methodology describes the process, but does not explain why the process takes the form that it does. I present nine “laws of data mining”, useful maxims for data miners, with explanations that reveal the reasons behind the surface properties of the data mining process. The nine laws have implications for predictive analytics applications: how and why it works so well, which ambitions could succeed, and which must fail.

     

    Speaker: Tom Khabaza, khabaza.com

     

    Top of this page ] [ Agenda overview ]


    12:15pm-1:30pm

    Lunch / Exhibits
    Room: Albert Suites


    1:30pm-2:25pm
    Expert Panel: Kaboom! Predictive Analytics Hits the Mainstream

    Predictive analytics has taken off, across industry sectors and across applications in marketing, fraud detection, credit scoring and beyond. Where exactly are we in the process of crossing the chasm toward pervasive deployment, and how can we ensure progress keeps up the pace and stays on target?

    This expert panel will address:

    • How much of predictive analytics’ potential has been fully realized?
    • Where are the outstanding opportunities with greatest potential?
    • What are the greatest challenges faced by the industry in achieving wide scale adoption?
    • How are these challenges best overcome?

     

    Panelist: John Elder, Ph.D., Elder Research, Inc.

    Panelist: Colin Shearer, WW Industry Solutions Leader, IBM UK Ltd

    Panelist: Udo Sglavo, Global Analytic Solutions Manager, SAS

    Panel moderator: Eric Siegel, Ph.D., Program Chair, Predictive Analytics World


    2:25pm-2:30pm

    Session Changeover


    2:30pm-3:20pm
    Crowdsourcing Data Mining
    Case Study: University of Melbourne, Chessmetrics
    Prediction Competitions: Far More Than Just a Bit of Fun

    Data modelling competitions allow companies and researchers to post a problem and have it scrutinised by the world’s best data scientists. There are an infinite number of techniques that can be applied to any modelling task but it is impossible to know at the outset which will be most effective. By exposing the problem to a wide audience, competitions are a cost effective way to reach the frontier of what is possible from a given dataset. The power of competitions is neatly illustrated by the results of a recent bioinformatics competition hosted by Kaggle. It required participants to pick markers in HIV’s genetic sequence that coincide with changes in the severity of infection. Within a week and a half, the best entry had already outdone the best methods in the scientific literature. This presentation will cover how competitions typically work, some case studies and the types of business modelling challenges that the Kaggle platform can address.

    Speaker: Anthony Goldbloom, Kaggle Pty Ltd

    Top of this page ] [ Agenda overview ]


    3:20pm-3:50pm

    Breaks /Exhibits
    Room: Albert Suites


    3:50pm-4:40pm
    Human Resources; e-Commerce
    Case Study: Naukri.com, Jeevansathi.com
    Increasing Marketing ROI and Efficiency of Candidate-Search with Predictive Analytics

    InfoEdge, India’s largest and most profitable online firm with a bouquet of internet properties has been Google’s biggest customer in India. Our team used predictive modeling to double our profits across multiple fronts. For Naukri.com, India’s number 1 job portal, predictive models target jobseekers most relevant to the recruiter. Analytical insights provided a deeper understanding of recruiter behaviour and informed a redesign of this product’s recruiter search functionality. This session will describe how we did it, and also reveal how Jeevansathi.com, India’s 2nd-largest matrimony portal, targets the acquisition of consumers in the market for marriage.

     

    Speaker: Suvomoy Sarkar, Chief Analytics Officer, HT Media & Info Edge India (parent company of the two companies above)

     

    Top of this page ] [ Agenda overview ]


    4:40pm-5:00pm
    Closing Remarks

    Speaker: Eric Siegel, Ph.D., Program Chair, Predictive Analytics World

    Top of this page ] [ Agenda overview ]


    Wednesday November 17, 2010

    Full-day Workshop
    The Best and the Worst of Predictive Analytics:
    Predictive Modeling Methods and Common Data Mining Mistakes

    Click here for the detailed workshop description

    • Workshop starts at 9:00am
    • First AM Break from 10:00 – 10:15
    • Second AM Break from 11:15 – 11:30
    • Lunch from 12:30 – 1:15pm
    • First PM Break: 2:00 – 2:15
    • Second PM Break: 3:15 – 3:30
    • Workshop ends at 4:30pm

    Speaker: John Elder, Ph.D., CEO and Founder, Elder Research, Inc.

     

    Interview John F Moore CEO The Lab

    Social Media Landscape

    Here is an interview with John F Moore, social media adviser,technologist and founder and CEO of The Lab.

    Ajay-  The internet seems to be crowded by social media experts with everyone who spends a lot of time on the internet claiming to be one? How  does a small business owner on a budget distinguish for the correct value proposition that social media can give them. 

    John- You’re right.  It seems like everytime I turn around I bump into more social media “experts”.  The majority of these self-proclaimed experts are not adding a great deal of value.  When looking to spend money for help ask the person a few questions about their approach. Things you should be hearing include:

    • The expert should be seeking to fully understand your business, your goals, your available resources, etc..
    • The expert should be seeking to understand current management thinking about social media and related technologies.

    If the expert is purely focused on tools they are the wrong person.  Your solution may require tools alone but they cannot know this without first understanding your business.

    Ajay- Facebook has 600 million people, with people preferring to play games and connect to old acquaintances rather than use social media for tangible career or business benefit..

    John- People are definitely spending time playing games, looking at photos, and catching up with old friends.  However, there are many businesses seeing real value from Facebook (primarily by tying it into their e-mail marketing and using coupons and other incentives).  For example, I recently shared a small case study (http://thejohnfmoore.com/2010/10/07/email-social-media-and-coupons-makes-the-cfo-smile/) where a small pet product company achieved a 22% bump in monthly revenue by combining Facebook and coupons together.  In fact,45% of this bump in revenue came from new clients.  Customer acquisition and increased revenue were accomplished by using Facebook for their business.
    Ajay-  How does a new social media convert (individual) go on selecting communities to join (Facebook,Twitter,Linkedin,Ning, Ping,Orkut, Empire Avenue etc etc.
    How does a small business owner take the same decision.

    John- It always starts with taking the time to define your goals and then determine how much time and effort you are willing to invest.  For example:
    • LinkedIn. A must have for individuals as it is one of the key social networking communities for professional networking.  Individuals should join groups that are relevant to their career and invest an hour a week.  Businesses should ensure they have a business profile completed and up to date.
    • Facebook can be a challenge for anyone trying to walk the personal/professional line.  However, from a business standpoint you should be creating a Facebook page that you can use to compliment your other marketing channels.
    • Twitter.  It is a great network to learn of, to meet, and to interact with people from around the world.  I have met thousands of interesting people, many of which I have had the pleasure to meet with in real life.  Businesses need to invest in listening on twitter to determine if their customers (current or potential) or competitors are already there discussing them, their marketplace, or their offerings.
    In all cases I would encourage businesses to setup social media accounts on LinkedIn, Facebook, Twitter, YouTube, and Flickr.  You want to ensure your brand is protected by owning these accounts and ensuring at least the base information is accurate.
    Ajay- Name the top 5 points that you think make a social media community successful.  What are the top 5 points for a business to succeed in their social media strategy.

    John-
    • Define your goals up front.  Understand why you are building a community and keep this goal in mind.
    • Provide education.  Ideally you want to become a thought leader in your space, the trusted resource that people can turn to even if they are not using your product or services today.
    • Be honest.  We all make mistakes.  When you do, be honest with your community and engage them in any fall-out that may be coming out of your mistake.
    • Listen to them.  Use platforms like BubbleIdeas to gather feedback on what your community is looking for from the relationship.
    • Measure.  Are you on track with your goals?  Do your goals need to change?
    Ajay- What is the unique value proposition that “The Lab” offers

    John- The Lab understands the strategic importance of leveraging social media, management and leadership best practices, and our understanding of local government and small and medium business to help people in these areas achieve their goals.  Too many consultants come to the table with a predefined solution that really misses the mark as it lacks understanding of the client’s goals.
    Ajay-  What is “CityCamp in Boston” all about.

    John- CityCamp is a FREE unconference focused on innovation for municipal governments and community organizations (http://www.citycampboston.org/what-is-citycamp-boston/).  It brings together politicians, local municipal employees, citizens, vendors, developers, and journalist to build a common understanding of local government challenges and then works to deliver measurable outcomes following the event.  The key is the focus on change management, driving change as opposed to just in the moment education.
    Biography-

    John F Moore is the Founder and CEO of The Lab (http://thelabinboston.com).  John has experience working with local governments and small and medium business owners to achieve their goals.  His experience with social media strategies, CRM, and a plethora of other solutions provides immense value to all of our clients.   He has built engineering organizations, learned sales and marketing, run customer service teams, and built and executed strategies for social media thought leadership and branding.  He is also a prolific blogger as you can see by checking out his blog at http://thejohnfmoore.com.

    India to make own DoS -citing cyber security

    After writing code for the whole world, Indian DoD (Department of Defense) has decided to start making it’s own Operating System citing cyber security. Presumably they know all about embedded code in chips, sneak kill code routines in dependent packages in operating system, and would not be using Linus Trovald’s original kernel (maybe the website was hacked to insert a small call k function 😉

    as the ancient Chinese said- May you live in interesting times. Still cyber wars are better than real wars- and StuxNet virus is but a case study why countries can kill enemy plans without indulging in last century tactics.

    Source-Manick Sorcar, The great Indian magician

    http://www.manicksorcar.com/cartoon33.jpg

    http://timesofindia.indiatimes.com/tech/news/software-services/Security-threat-DRDO-to-make-own-OS/articleshow/6719375.cms

    BANGALORE: India would develop its own futuristic computer operating system to thwart attempts of cyber attacks and data theft and things of that nature, a top defence scientist said.

    Dr V K Saraswat, Scientific Adviser to the Defence Minister, said the DRDO has just set up a software development  centre each here and in Delhi, with the mandate develop such a system. This “national effort” would be spearheaded by the  Defence Research and Development Organisation (DRDO) in partnership with software companies in and around Bangalore,  Hyderabad and Delhi as also academic institutions like Indian Institute of Science Bangalore and IIT Chennai, among others.

    “There are many gaps in our software areas; particularly we don’t have our own operating system,” said  Saraswat, also Director General of DRDO and Secretary, Defence R & D. India currently uses operating systems developed by western countries.

    Read more: Security threat: DRDO to make own OS – The Times of India http://timesofindia.indiatimes.com/tech/news/software-services/Security-threat-DRDO-to-make-own-OS/articleshow/6719375.cms#ixzz1227Y3oHg