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Over a decade long career , I have often been reminded of this saying from erstwhile mentors in long forgotten consulting email group- It is not WHAT you KNOW, it is WHO you KNOW. The power of WHO you KNOW can defeat even what you know , have learnt or worked hard at. Accordingly these are some wry observations on how businesses sometimes take shortcuts in India, and the whys and wherefores.
1) Regulatory Arbitrage due to Lack of Regulatory Oversight- This is especially true in terms of labor practices. This includes under-paying Caucasians and non -Indians for internships , or jobs (in the name of sponsoring the work visa). India is an extremely inexpensive place to stay in, but it is sometimes unfriendly (in terms of laws not people) to people visiting from the West. This ranges from amusing things to paying 10 times the price for non Indian visitors to Taj Mahal- to not so funny things as paying them lower salaries because they need a reason to stay on. Unfortunately this is true in many countries -underpaying aliens, but it is much better regulated in the West.
2) Stealing Intellectual Property- I have often known people to steal presentations and even excel macros from the place they were working to the new place. Almost no one gets prosecuted for intellectual property theft (unless you are caught with 10,000 pirated music or film cds)
3) Using Pirated Softwares – Lack of awareness of FOSS means many SMEs use shortcuts including downloading software from Pirate Bay and using this to work for clients in the West. Example- This could be as simple as downloading SAS software from Internet, or using WPS software for training and mis-representing SAS Institute’s name. (added confusion due to SAS -software,company,language ) . There are other major companies who suffer from this too, notably Microsoft.
This could be as complex as using academic versions of enterprise software for businesses purposes. In each case because of the geography, legal risk is quite low, and returns quite high from pirated software. It also helps lower the unethical vendor’s quotation of prices compared to the one who is doing it straight.
One way to avoid this is -ask your vendor to show you copy of how many legal licence’s for software. It can also help in cutting down exaggerated bench strength claims of vendors, as sometimes businesses hire many people and then put them on internal projects.
4) Illegal Trade practices- This include making employees sign a 1 year bond for not leaving the company after they have visited the West for company work- in the name of training . This also includes abusing the loopholes in various types of visa.
5) Ignoring signed contracts and negotiating to lower prices at every step illegally, in collusion with other vendors ( there is no effective anti -trust act ) and using the complete inadequate and lengthy nature of filing court cases in India.
Almost every non Indian client I know pays on time- almost every Indian client I know needs reminders. This is more of a mindset problem , knowing the reluctance to file lawsuits in India given slow progress in the courts ( India has 1.2 billion people and per capita access to judges and lawyers is quite low). The buzz word is- How much can we settle this? Lets do a settlement!
In the long run, this is choking off growth and potential of SMEs in India. In a continuing series- I will help the non Indian users with ways to use technology for legal remedies in India for intellectual property along with known case studies and examples.
I quite like Google’s monthly email on account activity. It is the Google way to offer free services, as well as treat users as special, that continues to command loyalty despite occasional exasperation with corporate thingies.
See this dashboard-
The medium range font shows persons sent/from statistics, and the color shades are done to empahsize or de-emphasize the metric
Colors used are black/grey, green and blue coincident with the Corporate Logo.
However some of the JS for visualizations need to be tweaked. Clearly the hover script ( an integral part of Dashboard design ) needs better elucidiation or formatting)
I would also venture my neck and suggest that rather than just monthly snapshots, atleast some way of comparing snapshots across periods or even the total time period be enabled- rather than be in seperate views. This may give the user a bit more analytical value.
Overall, a nice and simple dashboard which may be of some use to the business user who makes or views a lot of reports on online properties. Minimal and effective- and in keeping with Open Data- Data Liberation Principles. I guess Google is secure in the knowledge that users do not view time spent on Google services as a total waste , unlike some of the other more social websites they spend time on.
UPDATED POST- Some Models I use for Business Strategy- to analyze the huge reams of qualitative and uncertain data that business generates.
- Porters 5 forces Model-To analyze industries
- BCG Matrix- To analyze Product Portfolios
- Porters Diamond Model- To analyze locations
- McKinsey 7 S Model-To analyze teams
- Gernier Theory- To analyze growth of organization
- Herzberg Hygiene Theory- To analyze soft aspects of individuals
- Marketing Mix Model- To analyze marketing mix.
- The publisher adds credibility to your work
- A self fulfilling prophecy where researchers want to publish in exclusive journals and closed -access books, for the sole reason that others did so as well before them and thereby donate their knowledge and money to the publisher
The dichotomy in being a writer on open source with a non-open access publisher?
- I write on open source R ,
- and I have been published (one book )
- and am on contract to write two more ( R for Cloud Computing) and (R for Web and Social Media Analytics)
- My publisher does have open access journals.
- But the book is at $50. Most of India lives at less than 2$ per day. Thats 800 million people in my country alone.
But the publisher is the most reputed in this field. So what are my choices? How do I get more people to have choices to read books.
Take open knowledge , curate it, and turn it behind a $50 paywall. I am sorry, Aaron. People like me are the reason ……
I really liked the initiatives at JMP/Academic. Not only they offer the software bundled with a textbook, which is both good common sense as well as business sense given how fast students can get confused
(Rant 1 Bundling with textbooks is something I think is Revolution Analytics should think of doing instead of just offering the academic version for free downloading- it would be interesting to see the penetration of R academic market with Revolution’s version and the open source version with the existing strategy)
Major publishers of introductory statistics textbooks offer a 12-month license to JMP Student Edition, a streamlined version of JMP, with their textbooks.
and a glance through this http://www.jmp.com/academic/pdf/jmp_se_comparison.pdf shows it is a credible and not extremely whittled down version which would be just dishonest.
And I loved this Reference Card at http://www.jmp.com/academic/pdf/jmp10_se_quick_guide.pdf
Oracle, SAP- Hana, Revolution Analytics and even SAS/STAT itself can make more reference cards like this- elegant solutions for students and new learners!
More- creative-rants Honestly why do corporate sites use PDFs anymore when they can use Instapaper , or any of these SlideShare/Scribd formats to show information in a better way without diverting the user from the main webpage.
But I digress, back to JMP
Resources for Faculty Using JMP® Student Edition
Faculty who select a JMP Student Edition bundle for their courses may be eligible for additional resources, including course materials and training.
Special JMP® Student Edition for AP Statistics
JMP Student Edition is available in a convenient five-year license for qualified Advanced Placement statistics programs.
Try and have a look yourself at http://www.jmp.com/academic/student.shtml
Analytics 2012 Conference
SAS and more than 1,000 analytics experts gather at
Analytics 2012 Conference Details
Pre-Conference Workshops – Oct 7
Conference – Oct 8-9
Post-Conference Training – Oct 10-12
Caesars Palace, Las Vegas
The following are confirmed keynote speakers for Analytics 2012. Since he co-founded SAS in 1976, Jim Goodnight has served as the company’s Chief Executive Officer.
Dr. William Hakes is the CEO and co-founder of Link Analytics, an analytical technology company focused on mobile, energy and government verticals.
Tim Rey has written over 100 internal papers, published 21 external papers, and delivered numerous keynote presentations and technical talks at various quantitative methods forums. Recently he has co-chaired both forecasting and data mining conferences. He is currently in the process of co-writing a book, Applied Data Mining for Forecasting.
Plan to come to Analytics 2012 a day early and participate in one of the pre-conference workshops or take a SAS Certification exam. Prices for all of the preconference workshops, except for SAS Sentiment Analysis Studio: Introduction to Building Models and the Business Analytics Consulting Workshops, are included in the conference package pricing. You will be prompted to select your pre-conference training options when you register.
Sunday Morning Workshop
SAS Sentiment Analysis Studio: Introduction to Building Models
This course provides an introduction to SAS Sentiment Analysis Studio. It is designed for system designers, developers, analytical consultants and managers who want to understand techniques and approaches for identifying sentiment in textual documents.
Sunday, Oct. 7, 8:30a.m.-12p.m. – $250
Sunday Afternoon Workshops
Business Analytics Consulting Workshops
This workshop is designed for the analyst, statistician, or executive who wants to discuss best-practice approaches to solving specific business problems, in the context of analytics. The two-hour workshop will be customized to discuss your specific analytical needs and will be designed as a one-on-one session for you, including up to five individuals within your company sharing your analytical goal. This workshop is specifically geared for an expert tasked with solving a critical business problem who needs consultation for developing the analytical approach required. The workshop can be customized to meet your needs, from a deep-dive into modeling methods to a strategic plan for analytic initiatives. In addition to the two hours at the conference location, this workshop includes some advanced consulting time over the phone, making it a valuable investment at a bargain price.
Sunday, Oct. 7; 1-3 p.m. or 3:30-5:30 p.m. – $200
Demand-Driven Forecasting: Sensing Demand Signals, Shaping and Predicting Demand
This half-day lecture teaches students how to integrate demand-driven forecasting into the consensus forecasting process and how to make the current demand forecasting process more demand-driven.
Sunday, Oct. 7; 1-5 p.m.
Forecast Value Added Analysis
Forecast Value Added (FVA) is the change in a forecasting performance metric (such as MAPE or bias) that can be attributed to a particular step or participant in the forecasting process. FVA analysis is used to identify those process activities that are failing to make the forecast any better (or might even be making it worse). This course provides step-by-step guidelines for conducting FVA analysis – to identify and eliminate the waste, inefficiency, and worst practices from your forecasting process. The result can be better forecasts, with fewer resources and less management time spent on forecasting.
Sunday, Oct. 7; 1-5 p.m.
SAS Enterprise Content Categorization: An Introduction
This course gives an introduction to methods of unstructured data analysis, document classification and document content identification. The course also uses examples as the basis for constructing parse expressions and resulting entities.
Sunday, Oct. 7; 1-5 p.m.
Introduction to Data Mining and SAS Enterprise Miner
This course serves as an introduction to data mining and SAS Enterprise Miner for Desktop software. It is designed for data analysts and qualitative experts as well as those with less of a technical background who want a general understanding of data mining.
Sunday, Oct. 7, 1-5 p.m.
Modeling Trend, Cycles, and Seasonality in Time Series Data Using PROC UCM
This half-day lecture teaches students how to model, interpret, and predict time series data using UCMs. The UCM procedure analyzes and forecasts equally spaced univariate time series data using the unobserved components models (UCM). This course is designed for business analysts who want to analyze time series data to uncover patterns such as trend, seasonal effects, and cycles using the latest techniques.
Sunday, Oct. 7, 1-5 p.m.
SAS Rapid Predictive Modeler
This seminar will provide a brief introduction to the use of SAS Enterprise Guide for graphical and data analysis. However, the focus will be on using SAS Enterprise Guide and SAS Enterprise Miner along with the Rapid Predictive Modeling component to build predictive models. Predictive modeling will be introduced using the SEMMA process developed with the introduction of SAS Enterprise Miner. Several examples will be used to illustrate the use of the Rapid Predictive Modeling component, and interpretations of the model results will be provided.
Sunday, Oct. 7, 1-5 p.m
Ajay- Why did you choose Rapid Miner and R? What were the other software alternatives you considered and discarded?
Analyst- We considered most of the other major players in statistics/data mining or enterprise BI. However, we found that the value proposition for an open source solution was too compelling to justify the premium pricing that the commercial solutions would have required. The widespread adoption of R and the variety of packages and algorithms available for it, made it an easy choice. We liked RapidMiner as a way to design structured, repeatable processes, and the ability to optimize learner parameters in a systematic way. It also handled large data sets better than R on 32-bit Windows did. The GUI, particularly when 5.0 was released, made it more usable than R for analysts who weren’t experienced programmers.
Ajay- What analytics do you do think Rapid Miner and R are best suited for?
Analyst- We use RM+R mainly for sports analysis so far, rather than for more traditional business applications. It has been quite suitable for that, and I can easily see how it would be used for other types of applications.
Ajay- Any experiences as an enterprise customer? How was the installation process? How good is the enterprise level support?
Analyst- Rapid-I has been one of the most responsive tech companies I’ve dealt with, either in my current role or with previous employers. They are small enough to be able to respond quickly to requests, and in more than one case, have fixed a problem, or added a small feature we needed within a matter of days. In other cases, we have contracted with them to add larger pieces of specific functionality we needed at reasonable consulting rates. Those features are added to the mainline product, and become fully supported through regular channels. The longer consulting projects have typically had a turnaround of just a few weeks.
Ajay- What challenges if any did you face in executing a pure open source analytics bundle ?
Analyst- As Rapid-I is a smaller company based in Europe, the availability of training and consulting in the USA isn’t as extensive as for the major enterprise software players, and the time zone differences sometimes slow down the communications cycle. There were times where we were the first customer to attempt a specific integration point in our technical environment, and with no prior experiences to fall back on, we had to work with Rapid-I to figure out how to do it. Compared to the what traditional software vendors provide, both R and RM tend to have sparse, terse, occasionally incomplete documentation. The situation is getting better, but still lags behind what the traditional enterprise software vendors provide.
Ajay- What are the things you can do in R ,and what are the things you prefer to do in Rapid Miner (comparison for technical synergies)
Analyst- Our experience has been that RM is superior to R at writing and maintaining structured processes, better at handling larger amounts of data, and more flexible at fine-tuning model parameters automatically. The biggest limitation we’ve had with RM compared to R is that R has a larger library of user-contributed packages for additional data mining algorithms. Sometimes we opted to use R because RM hadn’t yet implemented a specific algorithm. The introduction the R extension has allowed us to combine the strengths of both tools in a very logical and productive way.
In particular, extending RapidMiner with R helped address RM’s weakness in the breadth of algorithms, because it brings the entire R ecosystem into RM (similar to how Rapid-I implemented much of the Weka library early on in RM’s development). Further, because the R user community releases packages that implement new techniques faster than the enterprise vendors can, this helps turn a potential weakness into a potential strength. However, R packages tend to be of varying quality, and are more prone to go stale due to lack of support/bug fixes. This depends heavily on the package’s maintainer and its prevalence of use in the R community. So when RapidMiner has a learner with a native implementation, it’s usually better to use it than the R equivalent.