Take up the White Man’s burden–Send forth the best ye breed–
Go bind your sons to exile To serve your captives’ need;
To wait in heavy harness, On fluttered folk and wild–
Your new-caught, sullen peoples, Half-devil and half-child.
Take up the White Man’s burden–In patience to abide,
To veil the threat of terror And check the show of pride;
By open speech and simple, An hundred times made plain
To seek another’s profit, And work another’s gain.
Take up the White Man’s burden– The savage wars of peace–
Fill full the mouth of Famine And bid the sickness cease;
And when your goal is nearest The end for others sought,
Watch sloth and heathen Folly Bring all your hopes to nought.
Take up the White Man’s burden–No tawdry rule of kings,
But toil of serf and sweeper–The tale of common things.
The ports ye shall not enter,The roads ye shall not tread,
Go mark them with your living,And mark them with your dead.
Take up the White Man’s burden–And reap his old reward:
The blame of those ye better,The hate of those ye guard–
The cry of hosts ye humour (Ah, slowly!) toward the light:–
“Why brought he us from bondage, Our loved Egyptian night?”
Take up the White Man’s burden–Ye dare not stoop to less–
Nor call too loud on Freedom To cloke your weariness;
By all ye cry or whisper, By all ye leave or do,
The silent, sullen peoples Shall weigh your gods and you.
Take up the White Man’s burden– Have done with childish days–
The lightly proferred laurel, The easy, ungrudged praise.
Comes now, to search your manhood Through all the thankless years
Cold, edged with dear-bought wisdom, The judgment of your peers!
This famous poem, written by Britain‘s imperial poet, was a response to the American take over of the Phillipines after the Spanish-American War.(published in 1899)
In my interactions with the world at large (mostly online) in the ways of data, statistics and analytics- I come across people who like to call themselves analysts.
As per me, there are 4 kinds of analysts principally,
1) Corporate Analysts- They work for a particular software company. As per them their product is great and infallible, their code has no bugs, and last zillion customer case studies all got a big benefit by buying their software.
They are very good at writing software code themselves, unfortunately this expertise is restricted to MicrosoftOutlook (emails) and MS Powerpoint ( presentations). No they are more like salesmen than analysts, but as Arthur Miller said ” All salesmen (person) are dreamers. When the dream dies, the salesman (person) dies (read transfers to bigger job at a rival company)
2) Third -Party Independent Analsyst- The main reason they are third party is they can not be tolerated in a normal corporate culture, their spouse can barely stand them for more than 2 hours a day, and their Intelligence is not matched by their emotional maturity. Alas, after turning independent analysts, they realize they are actually more dependent to people than before, and they quickly polish their behaviour to praise who ever is sponsoring their webinar, white paper , newsletter, or flying them to junkets. They are more of boutique consultants, but they used to be quite nifty at writing code, when younger, so they call themselves independent and “Noted Industry Analyst”
3) Researcher Analysts- They mostly scrape info from press releases which are mostly written by a hapless overworked communications team thrown at a task at last moment. They get into one hour call with who ever is the press or industry/analyst relations honcho is- turn the press release into bullet points, and publish on the blog. They call this as research Analysts and give it away for free (but actually couldnt get anyone to pay for it for last 4 years). Couldnt write code if their life depended on it, but usually will find transformation and expert somehwere in their resume/about me web page. May have co -authored a book, which would have gotten them a F for plagiarism had they submitted it as a thesis.
4) Analytical Analysts- They are mostly buried deep within organizational bureaucracies if corporate, or within partnerships if they are independent. Understand coding, innovation (or creativity). Not very aggressive at networking unless provoked by an absolute idiot belonging to first three classes of industry analyst. Prefer to read Atlas Shrugged than argue on business semantics.
Next time you see an industry expert- you know which cluster to classify them 😉
The United States Government is planning a new initiative at providing employable skills to people, to cope with unemployment. One skill perpetually in shortage is analytics training along with skills in statistics.
It is time that corporates like IBMSPSS, SAS Institute and Revolution Analytics as well as offshore companies in India or Asia can ramp up their on demand trainings, certification as well as academic partnership bundles. Indeed offshroing companies can earn revenue as well as goodwill if they help in with trainers available via video- conferencing. The new Deal initiative would require creative thinking as well as direct top management support to focus their best internal brains at developing this new revenue stream. Again the company that trains the most users (be it Revolution for R, IBM for SPSS-Cognos, SAS Institute for Base SAS-JMP, WPS for SAS language) is going to get a bigger chunk of new users and analysts.
Analytics skills are hot. There is big new demand for hot new skills by millions of unemployed Americans and Asians. How do you think this services market will play out?
If the US government could pump 800 Billion for bailouts, how much is your opinion it should spend on training programs to help citizens compete globally?
The national program is a response to frustrations from both workers and employers who complain that public retraining programs frequently do not provide students with employable skills. This new initiative is intended to help better align community college curriculums with the demands of local companies.
In tough economic times, it is more important than ever that companies be able to make better decisions using analytics. SAS is involved in two programs this summer that offer MBAs and unemployed technology workers the opportunity to learn and enhance analytics skills, and increase their marketability.
SAS is a partner in TechEngage, a week-long program of training classes that offer unemployed technology professionals new skills at a low cost to help them compete effectively in the marketplace.”
. “Fordham has a long history of collaboration with IBM that has brought innovative new skills to our curriculum to prepare students for future jobs. With this effort, Fordham is preparing students with marketable skills for a coming wave of jobs in healthcare, sustainability, and social services where analytics can be applied to everyday challenges.”
and R
Well TIBCO and Revolution ….hmmm…mmmm
I am not sure there is even a R Analytics Certification program at the least.
It has been postulated that wealth is simply a function of your ability to handle numbers as well as recall memory.
That is – answering just three numerical questions for Retirement/ people with age above 50 years. This alone should serve as a wake up call for greater investment in Education (than just banks and corporations).
Citation- NBER
Cognition and Economic Outcomes
Household wealth is strongly associated with numeracy and memory recall.
In Cognition and Economic Outcomes in the Health and Retirement Survey, (NBER Working Paper No. 15266), co-authors John McArdle, James Smith, and Robert Willis show that the ability to answer three simple mathematical questions is a significant predictor of wealth, wealth growth, and wealth composition for people over 50 years of age.
Using data from the Health and Retirement Survey (HRS) — a nationally representative longitudinal survey for the United States, which combines comprehensive information on household wealth with “cognition variables” designed to measure memory, intactness of mental status, numerical reasoning, broad numeracy, and vocabulary — these authors find that household wealth is strongly associated with numeracy and memory recall.
To test memory recall, respondents listened to a list of ten simple nouns, answered other questions for five minutes, and then were asked to recall as many of the nouns as possible. Two-thirds of the HRS survey respondents were able to recall between three and seven of the words. Most respondents answered just one of the three numeric questions correctly.
Answering a numeric question correctly in the three-question sequence was associated with a $20,000 increase in total household wealth and about a $7,000 increase in total financial wealth. Wealth also tended to increase with a higher numeracy score for either spouse in a married couple—when neither spouse answered any numeric questions correctly, which was about 10 percent of the cases, household wealth was about $200,000. When both spouses answered all questions correctly, household wealth was about $1,700,000.
In households where one spouse, the financial respondent, was in charge of finances, household financial wealth was larger if the financial respondent had the higher numeracy score. Answering a question correctly was associated with a $30,000 increase in household wealth if the financial respondent answered correctly and only a $10,000 increase if the non-financial respondent answered correctly. Households with higher numeracy scores were also more likely to have higher fractions of their portfolios in stock.
In this sample, wealth was higher for couples than for single-person households, and lower for minorities than non-minorities. Wealth increased with age and family income, and rose steeply with education. In the HRS, median household wealth was $198,000, and 9 percent of that was held in stocks. Median total income was $37,000, and the typical sample member was a high school graduate.
The authors point out that their exploratory analysis has only established that specific cognitive measures are useful predictors of accumulated wealth and that they have not established causal pathways. It is possible, for example, that a lifetime interest in investments and the stock market can improve numerical ability. However, they note that the fact that numeracy seems to predict total and financial wealth at lower wealth quartiles where people are less likely to be active investors does seem to weigh against a purely reverse pathway from investments to cognitive ability.
— Linda Gorman
Speaking of Educational Programs I came across a good example on education in numeracy –
SAS Institute has been working in the field in the following manner- directly as provider of SAS® Curriculum Pathways®
Fully funded by SAS and offered at no cost to US educators and students, SAS Curriculum Pathways is designed to enhance student achievement and teacher effectiveness by providing Web-based curriculum resources in all the core disciplines: English, math, science, social studies/history and Spanish, to educators and students in grades 8-14 in virtual schools, home schools, high schools and community colleges.
I believe other statistical softwares (like RE Computing, IBM SPSS , etc ) can also donate a small part of their product portfolio to K12 education (not just college education) as well. Education is an area where software companies especially in the field of statistics and analytics, co-operation and co-mpetition can co-exist to enhance the pool of potential developers , users and enhance life skills in numeracy as well .
Footnotes (1) In percent, seasonally adjusted. Annual averages are available for Not Seasonally Adjusted data. (2) Number of jobs, in thousands, seasonally adjusted. (3) For production and nonsupervisory workers on private nonfarm payrolls, seasonally adjusted. (4) All items, U.S. city average, all urban consumers, 1982-84=100, 1-month percent change, seasonally adjusted. (5) Finished goods, 1982=100, 1-month percent change, seasonally adjusted. (6) All imports, 1-month percent change, not seasonally adjusted. (R) Revised (P) Preliminary
Here is an interview with Karen Lopez who has worked in data modeling for almost three decades and is a renowned data management expert in her field.
Data professionals need to know about the data domain in addition to the data structure domain – Karen Lopez
Ajay- Describe your career in science. How would you persuade younger students to take more science courses.
Karen- I’ve always had an interest in science and I attribute that to the great science teachers I had. I studied information systems at Purdue University though a unique program that focuses on systems analysis and computer technologies. I’m one of the few who studied data and process modeling in an undergraduate program 25+ years ago.
I believe that it is very important that we find a way of attracting more scientists to teach. In both the natural and computer sciences, it’s difficult for institutions to tempt scientists away from professional positions that offer much greater compensation. So I support programs that find ways to make that happen.
Ajay- If you had to give advice to a young person starting their career in BI and had to give them advice in just three points – what would they be?
Karen- Wow. It’s tough to think of just three things, but these are recommendations that I make often:
– Remember that every design decision should be made based on cost, benefit, and risk. If you can’t clearly describe these for every side of a decision, then you aren’t doing design; you are guessing.
– No one beside you is responsible for advancing your skills and keeping an eye on emerging practices. Don’t expect your employer to lay out a career plan that is in your best interest. That’s not their job. Data professionals need to know about the data domain in addition to the data structure domain. The best database or data warehouse design in the world is worse than uses useless if the how the data is processed is wrong. Remember to expand your knowledge about data, not just the data structures and tools.
– All real-world work involves collaboration and negotiation. There is no one right answer that works for every situation. Building your skills in these areas will pay off significantly.
Ajay- What do you think is the best way for a technical consultant and client to be on the same page regarding requirements. Which methodology or template have you used, and which has given you the most success.
Karen- While I’m a huge fan of modeling (data modeling and other modeling), I still think that giving clients a prototype or mockup of something that looks real to them goes a long way. We need to build tools and competencies to develop these prototypes quickly. It’s a lost art in the data world.
Ajay- What are the special incentives that make Canada a great place for tech entrepreneurs rather than say go to the United States. ( Note- Disclaimer I have family in Canada and study in the US)
Karen- I prefer not to think of this as an either-or decision. I immigrated to Canada from the US about 15 years ago, but most of our business is outside of Canada. I have enjoyed special incentives here in Canada for small businesses as well as special programs that allowed me to work in Canada as a technical professional before I moved here permanently.
Overall, I have found Canadian employers more open to sponsoring foreign workers and it is easier for them to do so than what my US clients experience. Having said that, a significant portion of my work over the last few years has been on global projects where we leverage online collaboration tools to meet our goals. The advent of these tools has made it much easier to work from wherever I am and to work with others regardless of their visa statuses.
Where a company forms is less tied to where one lives or works these days.
Ajay- Could you tell us more about the Zachman framework (apart from the wikipedia reference)? A practical example on how you used it on an actual project would be great.
Karen- Of course the best resource for finding out about the Zachman framework is from John Zachman himself http://www.zachmaninternational.com/index.php/home-article/13 . He offers some excellent courses and does a great deal of public speaking at government and DAMA events. I highly recommend anyone interested in the Framework to hear about it directly from him.
There are many misunderstandings about John’s intent, such as the myth that he requires big upfront modeling (he doesn’t), that the Framework is a methodology (it isn’t), or that it can only be used to build computer systems (it can be used for more than that).
I have used the Zachman Framework to develop a joint Business-IT Strategic Information Systems Plan as well as to inventory and track progress of multi-project programs. One interesting use was a paper I authored for the Canadian Information Processing Society (CIPS) on how various educational programs, specializations, and certifications map to the Zachman Framework. I later developed a presentation about this mapping for a Zachman conference.
For a specific project, the Zachman Framework allows business to understand where their enterprise assets are being managed – and how well they are managed. It’s not an IT thing; it’s an enterprise architecture thing.
Ajay- What does Karen Lopez do for fun when not at work, traveling, speaking or blogging.
Karen- Sometimes it seems that’s all I do. I enjoy volunteering for IT-related organizations such as DAMA and CIPS. I participate in the accreditation of college and university educational programs in Canada and abroad. As a member of data-related standards bodies, namely the Association for Retail Technology Standards and the American Dental Association, I help develop industry standard data models. I’ve also been a spokesperson for a CIPS program to encourage girls to take more math and science courses throughout their student careers so that they may have access to great opportunities in the future.
I like to think of myself as a runner; last year I completed my first half marathon, which I’d never thought was possible. I am studying Hindi and Sanskrit. I’m also a addicted to reading and am thankful that some of it I actually get paid to do.
Biography
Karen López is a Senior Project Manager at InfoAdvisors, Inc. Karen is a frequent speaker at DAMA conferences and DAMA Chapters. She has 20+ years of experience in project and data management on large, multi-project programs. Karen specializes in the practical application of data management principles. Karen is also the ListMistress and moderator of the InfoAdvisors Discussion Groups at http://www.infoadvisors.com. You can reach her at www.twitter.com/datachick
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