Analytics 2011 Conference

From http://www.sas.com/events/analytics/us/

The Analytics 2011 Conference Series combines the power of SAS’s M2010 Data Mining Conference and F2010 Business Forecasting Conference into one conference covering the latest trends and techniques in the field of analytics. Analytics 2011 Conference Series brings the brightest minds in the field of analytics together with hundreds of analytics practitioners. Join us as these leading conferences change names and locations. At Analytics 2011, you’ll learn through a series of case studies, technical presentations and hands-on training. If you are in the field of analytics, this is one conference you can’t afford to miss.

Conference Details

October 24-25, 2011
Grande Lakes Resort
Orlando, FL

Analytics 2011 topic areas include:

The Dilemma

Temptation and sorrow

Have marred many a talented tomorrow

Life s Paradox is that to truly enjoy it

you have to abstain from its pleasures

Touch but don’t grab

Sniff but don’t smell

Taste but don’t swallow

Bite but don’t eat

Be excited only with the boundaries

Of your cubicle, your ears, your fingers

It is a game and we don’t know who is playing us

But we play on, soldier on, shoulder on

Accept our limitations and our weakness with grace

Our bias our prejudices our preoccupation with taste

Instant gratification leads to distant falls

Nature burns for adequately thermo-stated halls

And we burn for our illusions

Preoccupied as we are with silly delusions

Of our own unique irreplacability

Look Ma, Ah can now manipulate my DNA

Mother laughs, still a child.

Will blunder and fall, before it learns to walk for a while.

Cognitive Biases exploited by Spammers and Phishers

"Keep Walking"

Since they day you arrive on this planet, you are programmed into accepting reality as good and bad.

Beautiful people good. Ugly people not good.

Fellow countrymen good. Fellow earthling not so good.

Same religion is good. Different religion is awkward.

These cognitive biases are exploited in social media in the following manner-

1) Same Name Bias- You like people of the same name as you. or people who remind you of your brothers name. or uncles name.

All that information is already known. Esp true on Linkedin.

2) Same Orientation Bias- People tend to react better to photos considered attractive of opposite sex / opposite preference. Especially true on Twitter and Facebook.

3) Nationality Bias- Israeli Americans tend to respond better to Jewish looking phishers who claim to be from Israel but are not. Ditto for Indians- Arabs etc. E|sp true on Linkedin and Facebook.

You are positively biased to people of same country or of friendly nation states and will likely accept invites/friend/poke

4) Same organization/ alumni bias- People at end of phishing attack will have higher response rate if proxy identity claims familiarity with organizations or schools attended. Especially true on Facebook and Linkedin.

5) Same interests/movies/books bias- Your likely response rate is higher to someone who has seen your profile page on Facebook for interests, and checked the RSS stream of your tweets for stuff you like.

Bias is just maths. Period.

Which software do we buy? -It depends

Software (novel)
Image via Wikipedia

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.

To be continued-

 

 

 

 

Business Analytics Analyst Relations /Ethics/White Papers

Curt Monash, whom I respect and have tried to interview (unsuccessfully) points out suitable ethical dilemmas and gray areas in Analyst Relations in Business Intelligence here at http://www.dbms2.com/2010/07/30/advice-for-some-non-clients/

If you dont know what Analyst Relations are, well it’s like credit rating agencies for BI software. Read Curt and his landscaping of the field here ( I am quoting a summary) at http://www.strategicmessaging.com/the-ethics-of-white-papers/2010/08/01/

Vendors typically pay for

  1. They want to connect with sales prospects.
  2. They want general endorsement from the analyst.
  3. They specifically want endorsement from the analyst for their marketing claims.
  4. They want the analyst to do a better job of explaining something than they think they could do themselves.
  5. They want to give the analyst some money to enhance the relationship,

Merv Adrian (I interviewed Merv here at http://www.dudeofdata.com/?p=2505) has responded well here at http://www.enterpriseirregulars.com/23040/white-paper-sponsorship-and-labeling/

None of the sites I checked clearly identify the work as having been sponsored in any way I found obvious in my (admittefly) quick scan. So this is an issue, but it’s not confined to Oracle.

My 2 cents (not being so well paid 😉 are-

I think Curt was calling out Oracle (which didnt respond) and not Merv ( whose subsequent blog post does much to clarify).

As a comparative new /younger blogger in this field,
I applaud both Curt to try and bell the cat ( or point out what everyone in AR winks at) and for Merv for standing by him.

In the long run, it would strengthen analyst relations as a channel if they separate financial payment of content from bias. An example is credit rating agencies who forgot to do so in BFSI and see what happened.

Customers invest millions of dollars in BI systems trusting marketing collateral/white papers/webinars/tests etc. Perhaps it’s time for an industry association for analysts so that individual analysts don’t knuckle down under vendor pressure.

It is easier for someone of Curt, Merv’s stature to declare editing policy and disclosures before they write a white paper.It is much harder for everyone else who is not so well established.

White papers can take as much as 25,000$ to produce- and I know people who in Business Analytics (as opposed to Business Intelligence) slog on cents per hour cranking books on R, SAS , webinars, trainings but there are almost no white papers in BA. Are there any analytics independent analysts who are not biased by R or SAS or SPSS or etc etc. I am not sure but this looks like a good line to  pursue 😉 – provided ethical checks and balances are established.

Personally I know of many so called analytics communities go all out to please their sponsors so bias in writing does exist (you cant praise SAS on a R Blogging Forum or R USers Meet and you cant write on WPS at SAS Community.org )

– at the same time someone once told me- It is tough to make a living as a writer, and that choice between easy money and credible writing needs to be respected.

Most sponsored white papers I read are pure advertisements, directed at CEOs rather than the techie community at large.

Almost every BI vendor claims to have the fastest database with 5X speed- and benchmarking in technical terms could be something they could do too.

Just like Gadget sites benchmark products, you can not benchmark BI or even BA products as it is written not to do so  in many licensing terms.

Probably that is the reason Billions are spent in BI and the positive claims are doubtful ( except by the sellers). Similarly in Analytics, many vendors would have difficulty justifying their claims or prices if they are subjected to a side by side comparison. Unfortunately the resulting confusion results in shoddy technology coming stronger due to more aggressive marketing.