A new report from Linux Foundation found significant growth trends for enterprise usage of Linux- which should be welcome to software companies that have enabled Linux versions of software, service providers that provide Linux based consulting (note -lesser competition, lower overheads) and to application creators.
Key Findings from the Report
• 79.4 percent of companies are adding more Linux relative to other operating systems in the next five years.
• More people are reporting that their Linux deployments are migrations from Windows than any other platform, including Unix migrations. 66 percent of users surveyed say that their Linux deployments are brand new (“Greenfield”) deployments.
• Among the early adopters who are operating in cloud environments, 70.3 percent use Linux as their primary platform, while only 18.3 percent use Windows.
• 60.2 percent of respondents say they will use Linux for more mission-critical workloads over the next 12 months.
• 86.5 percent of respondents report that Linux is improving and 58.4 percent say their CIOs see Linux as more strategic to the organization as compared to three years ago.
• Drivers for Linux adoption extend beyond cost: technical superiority is the primary driver, followed by cost and then security.
• The growth in Linux, as demonstrated by this report, is leading companies to increasingly seek Linux IT professionals, with 38.3 percent of respondents citing a lack of Linux talent as one of their main concerns related to the platform.
• Users participate in Linux development in three primary ways: testing and submitting bugs (37.5 percent), working with vendors (30.7 percent) and participating in The Linux Foundation activities (26.0 percent).
and from the report itself-
It is an interesting report (and for some reason in a blue font-making it more like a blue paper than a white paper)
Often I am asked by clients, friends and industry colleagues on the suitability or unsuitability of particular software for analytical needs. My answer is mostly-
It depends on-
1) Cost of Type 1 error in purchase decision versus Type 2 error in Purchase Decision. (forgive me if I mix up Type 1 with Type 2 error- I do have some weird childhood learning disabilities which crop up now and then)
Here I define Type 1 error as paying more for a software when there were equivalent functionalities available at lower price, or buying components you do need , like SPSS Trends (when only SPSS Base is required) or SAS ETS, when only SAS/Stat would do.
The first kind is of course due to the presence of free tools with GUI like R, R Commander and Deducer (Rattle does have a 500$ commercial version).
The emergence of software vendors like WPS (for SAS language aficionados) which offer similar functionality as Base SAS, as well as the increasing convergence of business analytics (read predictive analytics), business intelligence (read reporting) has led to somewhat brand clutter in which all softwares promise to do everything at all different prices- though they all have specific strengths and weakness. To add to this, there are comparatively fewer business analytics independent analysts than say independent business intelligence analysts.
2) Type 2 Error- In this case the opportunity cost of delayed projects, business models , or lower accuracy – consequences of buying a lower priced software which had lesser functionality than you required.
To compound the magnitude of error 2, you are probably in some kind of vendor lock-in, your software budget is over because of buying too much or inappropriate software and hardware, and still you could do with some added help in business analytics. The fear of making a business critical error is a substantial reason why open source software have to work harder at proving them competent. This is because writing great software is not enough, we need great marketing to sell it, and great customer support to sustain it.
As Business Decisions are decisions made in the constraints of time, information and money- I will try to create a software purchase matrix based on my knowledge of known softwares (and unknown strengths and weakness), pricing (versus budgets), and ranges of data handling. I will add in basically an optimum approach based on known constraints, and add in flexibility for unknown operational constraints.
I will restrain this matrix to analytics software, though you could certainly extend it to other classes of enterprise software including big data databases, infrastructure and computing.
Noted Assumptions- 1) I am vendor neutral and do not suffer from subjective bias or affection for particular software (based on conferences, books, relationships,consulting etc)
2) All software have bugs so all need customer support.
3) All software have particular advantages , strengths and weakness in terms of functionality.
4) Cost includes total cost of ownership and opportunity cost of business analytics enabled decision.
5) All software marketing people will praise their own software- sometimes over-selling and mis-selling product bundles.
Software compared are SPSS, KXEN, R,SAS, WPS, Revolution R, SQL Server, and various flavors and sub components within this. Optimized approach will include parallel programming, cloud computing, hardware costs, and dependent software costs.
From the good folks at AsterData, a webcast on a slightly interesting analytics topic
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His argument of love is not very original though it was first made by these four guys
I am going to argue that “some” R developers should be paid, while the main focus should be volunteers code. These R developers should be paid as per usage of their packages.
Let me expand.
Imagine the following conversation between Ross Ihaka, Norman Nie and Peter Dalgaard.
Norman- Hey Guys, Can you give me some code- I got this new startup.
Ross Ihaka and Peter Dalgaard- Sure dude. Here is 100,000 lines of code, 2000 packages and 2 decades of effort.
Norman- Thanks guys.
Ross Ihaka- Hey, What you gonna do with this code.
Norman- I will better it. Sell it. Finally beat Jim Goodnight and his **** Proc GLM and **** Proc Reg.
Ross- Okay, but what will you give us? Will you give us some code back of what you improve?
Norman – Uh, let me explain this open core …
Peter D- Well how about some royalty?
Norman- Sure, we will throw parties at all conferences, snacks you know at user groups.
Ross – Hmm. That does not sound fair. (walks away in a huff muttering)-He takes our code, sells it and wont share the code
Peter D- Doesnt sound fair. I am back to reading Hamlet, the great Dane, and writing the next edition of my book. I am glad I wrote a book- Ross didnt even write that.
Norman-Uh Oh. (picks his phone)- Hey David Smith, We need to write some blog articles pronto – these open source guys ,man…
———–I think that sums what has been going on in the dynamics of R recently. If Ross Ihaka and R Gentleman had adopted an open core strategy- meaning you can create packages to R but not share the original where would we all be?
At this point if he is reading this, David Smith , long suffering veteran of open source flameouts is rolling his eyes while Tal G is wondering if he will publish this on R Bloggers and if so when or something.
Lets bring in another R veteran- Hadley Wickham who wrote a book on R and also created ggplot. Thats the best quality, most often used graphics package.
In terms of economic utilty to end user- the ggplot package may be as useful if not more as the foreach package developed by Revolution Computing/Analytics.
However lets come to open core licensing ( read it here http://alampitt.typepad.com/lampitt_or_leave_it/2008/08/open-core-licen.html ) which is where the debate is- Revolution takes code- enhances it (in my opinion) substantially with new formats XDF for better efficieny, web services API, and soon coming next year a GUI (thanks in advance , Dr Nie and guys)
and sells this advanced R code to businesses happy to pay ( they are currently paying much more to DR Goodnight and HIS guys)
Why would any sane customer buy it from Revolution- if he could download exactly the same thing from http://r-project.org
Hence the business need for Revolution Analytics to have an enhanced R- as they are using a product based software model not software as a service model.
If Revolution gives away source code of these new enhanced codes to R core team- how will R core team protect the above mentioned intelectual property- given they have 2 decades experience of giving away free code , and back and forth on just code.
Now Revolution also has a marketing budget- and thats how they sponsor some R Core events, conferences, after conference snacks.
How would people decide if they are being too generous or too stingy in their contribution (compared to the formidable generosity of SAS Institute to its employees, stakeholders and even third party analysts).
Would it not be better- IF Revolution can shift that aspect of relationship to its Research and Development budget than it’s marketing budget- come with some sort of incentive for “SOME” developers – even researchers need grants and assistantships, scholarships, make a transparent royalty formula say 17.5 % of the NEW R sales goes to R PACKAGE Developers pool, which in turn examines usage rate of packages and need/merit before allocation- that would require Revolution to evolve from a startup to a more sophisticated corporate and R Core can use this the same way as John M Chambers software award/scholarship
Dont pay all developers- it would be an insult to many of them – say Prof Harrell creator of HMisc to accept – but can Revolution expand its dev base (and prospect for future employees) by even sponsoring some R Scholarships.
And I am sure that if Revolution opens up some more code to the community- they would the rest of the world and it’s help useful. If it cant trust people like R Gentleman with some source code – well he is a board member.
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Now to sum up some technical discussions on NeW R
1) An accepted way of benchmarking efficiencies.
2) Code review and incorporation of efficiencies.
3) Multi threading- Multi core usage are trends to be incorporated.
4) GUIs like R Commander E Plugins for other packages, and Rattle for Data Mining to have focussed (or Deducer). This may involve hiring User Interface Designers (like from Apple 😉 who will work for love AND money ( Even the Beatles charge royalty for that song)
5) More support to cloud computing initiatives like Biocep and Elastic R – or Amazon AMI for using cloud computers- note efficiency arguements dont matter if you just use a Chrome Browser and pay 2 cents a hour for an Amazon Instance. Probably R core needs more direct involvement of Google (Cloud OS makers) and Amazon as well as even Salesforce.com (for creating Force.com Apps). Note even more corporates here need to be involved as cloud computing doesnot have any free and open source infrastructure (YET)
“If something goes wrong with Microsoft, I can phone Microsoft up and have it fixed. With Open Source, I have to rely on the community.”
And the community, as much as we may love it, is unpredictable. It might care about your problem and want to fix it, then again, it may not. Anyone who has ever witnessed something online go “viral”, good or bad, will know what I’m talking about.
Sentiment analysis or opinion mining refers to a broad (definitionally challenged) area of natural language processing, computational linguistics and text mining. Generally speaking, it aims to determine the attitude of a speaker or a writer with respect to some topic. The attitude may be their judgment or evaluation (see appraisal theory), their affective state (that is to say, the emotional state of the author when writing) or the intended emotional communication (that is to say, the emotional effect the author wishes to have on the reader).
–SAS Sentiment Analysis delivers insights on customer, competitor and organizational opinions to a degree never before possible via manual review of electronic text. As a result, SAS, the leader in business analytics software and services, has earned the prestigious Communications Solutions Product of the Year Award fromTechnology Marketing Corporation (TMC).
“SAS has automated the time-consuming process of reading individual documents and manually extracting relevant information”
“SAS Sentiment Analysis has shown benefits for its customers and it provides ROI for the companies that use it,” said Rich Tehrani, CEO, TMC. “Congratulations to the entire team at SAS, a company distinguished by its dedication to software quality and superiority to address marketplace needs.”
Derive positive and negative opinions, evaluations and emotions
SAS Sentiment Analysis’ high-performance crawler locates and extracts sentiment from digital content sources, including mainstream websites, social media outlets, internal servers and incoming news feeds. SAS’ unique hybrid approach combines powerful statistical techniques with linguistics rules to improve accuracy to the detailed feature level. It summarizes the sentiment expressed in all available text collections – identifying trends and creating graphical reports that describe the expressed feelings of consumers, partners, employees and competitors in real time. Output from SAS Sentiment Analysis can be stored in document repositories, surfaced in corporate portals and used as input to additional SAS Text Analytics software or search engines to help decision makers evaluate trends, predict future outcomes, minimize risks and capitalize on opportunities.
“SAS has automated the time-consuming process of reading individual documents and manually extracting relevant information,” said Fiona McNeill, Global Analytics Product Marketing Manager at SAS. “Our integrated analytics framework helps organizations maximize the value of information to improve their effectiveness.”
SAS Sentiment Analysis is included in the SAS Text Analytics suite, which helps organizations discover insights from electronic text materials, associate them for delivery to the right person or place, and provide intelligence to select the best course of action. Whether answering complex search-and-retrieval questions, ensuring appropriate content is presented to internal or external constituencies, or predicting which activity or channel will produce the best effect on existing sentiments, SAS Text Analytics provides exceptional real-time processing speeds for large volumes of text.
SAS Text Analytics solutions are part of the SAS Business Analytics Framework, backed by the industry’s most comprehensive range of consulting, training and support services, ensuring customers maximum return from their IT investments.
Recognizing vision
The Communications Solutions Product of the Year Award recognizes vision, leadership and thoroughness. The most innovative products and services brought to the market from March 2008 through March 2009 were chosen as winners of this Product of the Year Award and are published on the INTERNET TELEPHONY and Customer Interaction Solutionswebsites.
1) Eastern Europe has definitely come up and so is China in basic outsourcing processes. For more complex processes India remains the primary destination and sometimes act as managers to East European and China new outsourcers.EU countries delivery centers enjoy less stringent data norms. The Chinese speak much worse English and are better mathematicians. So are the East Europeans.
Some of this out sourcing 2.0 is driven by Indian companies who want to mitigate risks of rupee and have global delivery 24 * 7 and also enjoy EU norms of data protection.
2) Cutting costs through open source software like R, better solutions like WPS could also get big.
You can also see fragmentation to consultants as technology like remote desktop and skype allows low risk remote working.
Consolidation of KPO and BPO has been problematic and disappointing in expectations at least in India.
Next big big trend depends on how 2008 US Recession and politics plays out as USA remains the biggest source of outsourcing business and trends in this field
DECISION STATS 