Bob Sutor

Partially rebuilding the kitchen porch

2013-05-18T18:26:07Z

Very long time readers may recall that in 2006 I built a new wooden porch off our kitchen door to replace some small concrete steps. It was a fun project, though it took longer than I expected. The structure of the porch is made of pressure treated wood, while the outer wood is plain and untreated other than being painted. Therein lay the problem, in one particular area.

If you look at the photo on the right, you see that the hand rails slant down and join to the bottom posts on the side of the posts. It looks nice. It also collects snow, ice, rain, and debris.

A couple of years ago I noticed that rot had begun to set into the top of the post on the left, and probably a bit on the right. Today I finally got around to repairing it. This is what the porch looks like mid-reconstruction:

Most of the wood on the up-step side of the left post was rotten. I was hoping to save some of the outer wood since I had routed decorative fluting into the sides, but the rot wrapped around on the bottom. So I made the decision to just rip it all out. The porch on the right did indeed have some rot, but I can repair that without complete replacement.

The handrail will also need to be replaced since the bottom end has too much rot:

I’m leaving it there for the moment until I put replacement on. I’ll need to unscrew all the spindles from the top and then screw the new rail onto them. I’ll use the old handrail as the pattern for the new.

My immediate plan is to let the pressure treated inner post dry out while I purchase some good quality treated 1x6s and a 1×4 for the outer post and the new hand rail. I’ll cut them roughly to size and let them dry out as well. This is necessary before I cut them to final size, angle the corners, and cut the new fluting. Then everything goes back together again.

When that is complete, I’ll cut some triangular pieces of wood and put them at the bottom of the handrails so that the rain and snow is diverted off to the sides. I’m hoping this is enough to save the post on the right from further damage.

© Robert S. Sutor for Bob Sutor, 2013. All rights reserved.
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Tagged with: carpentry, porch.
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Daily links for 05/14/2013

2013-05-14T16:30:15Z

How much does it cost to self-publish a book? Three budget breakdowns.

“For many writers considering self-publishing, cost is the first question and concern. The range authors spend to self-publish varies dramatically. You can choose to self-publish completely free doing everything yourself, or you can spend thousands upon thousands of dollars paying for printing, marketing and other services. The trick is find the happy medium of buying what you need and doing what you can on your own.”

tags: book publishing cost

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Daily links for 05/11/2013

2013-05-11T16:30:15Z

Open source Java iOS tools compared – JavaWorld

“Java programming for Apple’s iOS devices is not only possible but it’s getting easier all the time. Steve Hannah surveys the recent evolution of the Java iOS landscape, then introduces five open source Java iOS tools. Find out how Avian, Codename One, J2ObjC, RoboVM, and XMLVM resolve the challenges of Java iOS native client development for developers who are ready to go mobile. “

tags: java ios mobile

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Daily links for 05/08/2013

2013-05-08T16:30:14Z

The Linux desktop is already the new normal | Open Source Software – InfoWorld

“A debate is smoldering yet again in the Linux community as prominent figures debate whether it’s time to give up hope on the “year of the Linux desktop” ever coming or whether the advent of Android is actually its fulfillment. Problem is, it came and it’s been here a while, but we haven’t even noticed. We just didn’t know what it would look like.”

tags: linux desktop open source
Online Graphing Calculator: Plot your own SVG Math Graphs

tags: graphing math svg
Lessons From A Crash Course In Data Science ⚙ Co.Labs ⚙ code + community

“Data Scientist—technology’s hottest job title—I spent a month trying to figure out what, exactly, these mysterious new Masters of the Universe knew that I didn’t.”

tags: data science analytics
In-Depth: How To Pick The Right Revenue Model For Your App ⚙ Co.Labs ⚙ code + community

“It’s a common story these days: You have an awesome app idea, you raise a seed round, and your app gets a ton of loyal free users. Then you turn on pricing and everything comes crashing down. Now your app isn’t making money and your investors are pissed. What do you do?”

tags: app mobile

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Some questions to ask yourself if you want to be a data scientist

2013-05-08T00:05:41Z

Last October, the Harvard Business Review published an article called “Data Scientist: The Sexiest Job of the 21st Century.” I could virtually hear the rejoicing in the work hallways of analysts, mathematicians, statisticians, and computer scientists everywhere. At last, recognition!

While it is debatable in this case if the job really is sexy or even hip and will make you either, there’s really no question that the rise of analytics and big data are making these skills increasingly in demand. Is this the right job for you?

A good place to start to understand what is needed to be a data scientist is at the INFORMS Analytics Certification website. It costs money to get this, but the program information gives you an idea of the kinds of questions on the test, the sorts of case studies with which you should be comfortable, and the books and websites you can use for further learning.

In a more informal way, let me here ask some questions you should answer about yourself and your knowledge to see if this is a career or job you might consider. I’ve included a few technical questions to encourage you to learn more about some of the disciplines involved.

Do you suffer from math anxiety? Does solving equations, working with matrices, or making sense of table or graphs scare you? If so, this probably is not the field for you.
Are you comfortable with statistics? Could you in your spare time over the next month do what would equate to a first, solid, mathematically sound statistics course? Would you get an A for your efforts? You’ll need statistics to understand the data and to give yourself sanity checks about the conclusions you are drawing.
Is Microsoft Excel or OpenOffice Calc your favorite tool in your office productivity suite? Doing real analytics and big data often goes well beyond what you can do in a spreadsheet, but if this kind of software terrifies you, data science might not be a good match.
Do you know how services like Netflix choose what movies you would like to watch? Make an educated guess and then go learn some of the techniques. I won’t give you a reference, go explore what you find on the net.
Do you understand the differences between descriptive, diagnostic, predictive, and prescriptive analytics? Where does optimization fall among these?
Do you like saying the word “stochastic”? Do you know what it means?
Who was Andrey Markov and what was his obsession with chains?
What criteria and analysis would you use to predict who will win the next World Series, Super Bowl, or World Cup?
Under what situations would you use Hadoop, Hive, HBase, Pig, SPSS, R, or CPLEX?
How would you go about constructing your personal profile from all the public data about you on the web? This could be from yourself (e.g., your Twitter feed) or produced by others. Include your gender, your approximate age and income, the town in which you live, the high school to which you went, your hobbies, the name of your significant other, the number of children you have, your favorite color, your favorite sport, your best friend’s name, and the color of your hair. Does this scare you?
When can Twitter add to your insight about marketing campaigns and when does it just add unnecessary noise?

This is by no means an exhaustive list, but if these topics intrigue you, you have or are willing to get the technical background, and you know who Nate Silver is, you just might have a career in data science.

© Robert S. Sutor for Bob Sutor, 2013. All rights reserved.
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Tagged with: analytics, Big Data, data science.
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Math and Analytics at IBM Research: 50+ Years

2013-05-08T00:26:19Z

Soon after I arrived back in IBM Research last July after 13 years away in the Software Group and Corporate, I was shown a 2003 edition of the IBM Journal of Research and Development that was dedicated to the Mathematical Sciences group at 40. From that, I and others assumed that this year, 2013, was the 50th anniversary of the department.

I set about lining up volunteers to organize the anniversary events for the year and sent an email to our 300 worldwide members of what is now called the Business Analytics and Mathematical Sciences strategy area. Not long afterwards, I received a note from Alan Hoffman, a former director of the department, saying that he was pretty sure that the department had been around since 1958 or 59. So our 50th Anniversary became the 50+ Anniversary. Evidently mathematicians know the theory of arithmetic but don’t always practice it correctly

The first director of the department was Herman Goldstine who joined after working on the ENIAC computer and a stint at the Institute for Advanced Study in Princeton. Goldstine is pictured in the first photo on the right at a reception at the T.J. Watson Research Center in the early 1960s. Goldstine died in 2004, but all other directors of the department are still alive.

We decided that the first event of the year celebrating the (more than) half century of the department would be a reunion of the directors for a morning of panel discussions. This took place this last Wednesday, May 1, 2013.

Photo credit: Mary Beth Miller

I started the day by giving a glimpse of what the department looks like today: the above-mentioned 300 Ph.D.s, software engineers, postdocs, and other staff distributed over the areas of optimization, analytics, visual analytics, and social business in 10 of IBM’s 12 global labs.

I then introduced our panel pictured in the photo above. From left to right we have me, Brenda Dietrich, Bill Pulleyblank, Shmuel Winograd, Roy Adler (a mathematician who was in the department during the tenures of all the other directors except me), Alan Hoffman, Dick Toupin, Hirsh Cohen, and Ralph Gomory.

My goal for the discussion was to go back and look at some of the history and culture of the math department over the last five decades. I was hoping we would hear anecdotes and stories of what life was like, the challenges they faced, and the major successes and disappointments.

Other than a few questions I had prepared, I wasn’t sure where our conversation would go. The many researchers who joined us in the auditorium at the T. J. Watson Research Center in Yorktown Heights, NY, or via the video feed going out to the other worldwide labs would have a chance to ask questions near the end of the morning.

I’m not going to go over every question and answer but rather give you the gist of what we spoke about.

Ralph Gomory reminded us that the department was started in a much different time, during the Cold War. The problems they were trying to solve using the hardware and the software of the day were often related highly confidential. However, every era of the department has had its own focus, burning problems to be solved, and operational environment.
Hirsh Cohen got his inspiration for the mathematics he did by solving practical problems such as those related to the large mainframe-connected printers. Many people feel that mathematics shouldn’t stray too far from the concrete, but it is not that simple. This isn’t just applied mathematics, it is a way of looking for inspiration that may express itself in more theoretical ways. The panelists mentioned more than once that the original posers of business or engineering problems might not recognize the mathematics that was developed in response. (I think there is nothing wrong with theoretical mathematics with no direct connection to the physical world, but there are some areas of mathematical pursuit that I think are just silly and of marginal pure or applied interest.)
In response to my question about balancing business needs with the desire to advance basic science, Shmuel Winograd told me I had asked the wrong question: it was about the integration of business with basic science, not a partitioning of time or resources between them. This very much sets the tone of how you manage such a science organization in a commercial company. The successful integration of these concerns may also be why IBM Research is pretty much the sole survivor of the industrial research labs from the 1950s and 1960s.
There was general consensus that it is difficult to get a researcher to do science in an area that he or she fundamentally does not want to work. This was redirected to the audience members who were reminded to understand what they loved to do and then find a way to do it. (This sounded like a bit of a management challenge to me, and I suspect I’ll hear about it again.)
Time gives a great perspective on the quality and significance of scientific work that is just not obvious while you are the middle of it. This is one of the reasons why retrospectives such as this can be so satisfying.

Photo credit: Mary Beth Miller

After the first panel and coffee break, we came back and I started the session looking at the future of the department instead of the history. We have an internal department social network community in IBM Connections and I started by summarizing some of the suggestions people came up with about what we’ll be doing in the department in five, ten, and twenty years.

Sustainability, robotic applications of cognitive computing, and mathematical algorithms for quantum computing were all suggested. Note that his was all fun speculation, not strategy development!

Eleni Pratsini, Director of Optimization Research, and Chid Apte, Director of Analytics Research, then each discussed technical topics that could be future areas for scientific research as well as having significant business use.

After the final Q&A session, we got everyone on stage for a group photo.

Photo credit: Steve Hamm

One thing that struck me when we were doing the research through the archives was how much more of a record we have of the first decade of the department than we do of the 40+ years afterwards. In those early days, each department did a typed report of its activities which was then sent to management and archived.

With the increasing use of email and, much later, digital photos, we just don’t have easy if any access to what happened month by month. As part of this 50+ Anniversary, I’m going to organize an effort to do a better job of finding and cataloging the documents, photos, and video of the department.

This should make it easier for future celebrations of the department’s history. I suspect I’m not going to make it to the 100th anniversary, but I just might get to the 75th. For the record for those who come after me, that will be in 2034.

© Robert S. Sutor for Bob Sutor, 2013. All rights reserved.
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Tagged with: analytics, history, Mathematics.
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Daily links for 05/01/2013

2013-05-01T16:30:14Z

Kenneth I. Appel, Mathematician Who Harnessed Computer Power, Is Dead at 80 – NYTimes.com

“Kenneth I. Appel, who helped usher the venerable mathematical proof into the computer age, solving a longstanding problem concerning colors on a map with the help of an I.B.M. computer making billions of decisions, died on April 19 in Dover, N.H. He was 80.”

tags: mathematics

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Monthly disclaimer

2013-01-26T21:42:02Z

The postings on this site are my own and don’t necessarily represent my employer’s positions, strategies or opinions, especially if they are about the guitar, fishing, gardening, carpentry, porch building, and musical tastes.

Blog entries before 2010 are in my Archived Blog.

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Daily links for 04/28/2013

2013-04-28T16:30:24Z

How Big Data Is Playing Recruiter for Specialized Workers – NYTimes.com

“Of late, growing numbers of academics and entrepreneurs are applying Big Data to human resources and the search for talent, creating a field called work-force science.”

tags: hr analytics big data

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Daily links for 04/27/2013

2013-04-27T16:30:13Z

MathML Samples |

“This page contains sample equations represented by MathML markup. The page has been configured to always use HTML-CSS mode with web fonts to display the equations, which produces uniform layout and typesetting across browsers.”

tags: mathml JavaScript
MathML Central: A Wolfram Web Resource

tags: mathml
MathML for Math and Science Communication

“MathML is the XML standard for encoding mathematics. Originally intended as a means of incorporating mathematics in web pages, MathML has grown to become a general format for the exchange and communication of mathematics in a wide variety of math and science applications.”

tags: mathml
Chrome no longer supports MathML | The Aperiodical

“Recently we reported that Chrome has added support for MathML, a good method for representing maths on the web. Now a comment on a discussion about enabling MathML in Chromium, the open source web browser project from which Google Chrome draws its source code, has announced that this feature will be turned off, for now.”

tags: mathml

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Daily links for 04/24/2013

2013-04-24T16:30:17Z

Monty changes roles, goes big with MariaDB—and gains Wikipedia as a user | Ars Technica

“All of this comes as big Web players are taking a hard look at their database investments. The buzz around the “NoSQL” database movement has begun to see a backlash. Late last year, Google announced its own efforts to shift back toward SQL database technology with its Spanner distributed SQL database research. And many read-heavy websites (such as Ars, for instance) have moved back to MySQL and other open-source SQL databases after dalliances with NoSQL.”

tags: mysql mariadb

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Daily links for 04/23/2013

2013-04-23T16:30:18Z

With Tablets, Businesses Ring Up at More Fanciful Cash Registers – NYTimes.com

“With the advent of tablets, particularly the iPad, many stores have traded in their clunky cash registers for mobile devices. Now, though, they are dressing up those tablets with inventive accessories to make them both more pleasant to look at and more practical for cashiers.”

tags: tablets mobile retail

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Daily links for 04/02/2013

2013-04-02T16:30:14Z

IBM Information On Demand 2013 – global conference

November 3-7, Las Vegas, Nevada

tags: iod ibm analytics
Baseball Broadcasts Introduce Advanced Statistics, but With Caution – NYTimes.com

“Statistical analysis has swept through baseball over the past decade, becoming part of the fabric of the game and an object of growing fascination to its fans. As players, managers and front office executives embrace the esoteric statistics, teams increasingly want their radio announcers just as fluent in the language of WAR, VORP and B.A.B.I.P. “

tags: baseball sabermetrics

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Monthly disclaimer

2013-01-26T21:42:10Z

Blog entries before 2010 are in my Archived Blog.

Daily links for 03/26/2013

2013-03-26T16:30:17Z

Army scalability test finds login bottleneck

“Looking for an immersive platform for your company, non-profit, educational institution, or government agency? Start with the following list of vendors, all of which have a successful history of serving enterprise customers.”

tags: 3d opensim

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Daily links for 03/21/2013

2013-03-21T16:30:18Z

Python Software Foundation wins a battle for the Python name | Python – InfoWorld

“The Python Software Foundation (PSF) announced it has reached a settlement with POBox Hosting Ltd. of the United Kingdom over the latter’s trademark application for the term “Python” in connection with cloud hosting and its application for a figurative trademark in Europe incorporating the word “Python.” While the PSF owns the trademark for Python within the United States, it did not have an equivalent filing within the European Union.”

tags: python software

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Daily links for 03/09/2013

2013-03-09T16:30:18Z

Ned Batchelder: Python parsing tools

“A few years ago, I went looking for Python parsing tools. I spent a long time researching the various options. When I was done, I had a cheat sheet on the different alternatives. This is that cheat sheet, cleaned up a bit. It is very spotty. If you have updates to the information here, let me know. Because this is a compilation of factoids freely available on the web, it is in the public domain.”

tags: parser python parsing library
How Big Data is Transforming the Hunt for Talent – Forbes

““What we’ll find is a reinvention of some very traditional processes in companies and a rethinking of how HR gets done,” she says. “It’ll be underpinned by a fact base that will inform where the highest value is to be added.””

tags: talent
Samsung’s Galaxy S 4 to Appear in March: 10 Features to Expect

“So far, Samsung, taking a page from Apple’s marketing manual, has remained tight-lipped on its plans for the Galaxy S4. But just about everyone agrees that the product will be one that consumers and business users will to take a close look at.”

tags: samsung galaxy mobile

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Daily links for 03/08/2013

2013-03-08T16:30:14Z

Condé Nast’s VP of marketing analytics on how tablets changed publishing | ZDNet

“During the 2013 Adobe Summit this week, I had a chance to sit down with Chris Reynolds, vice president of marketing analytics at Condé Nast, to find out more about how one of the world’s largest and most well-known publishing companies is trying to get ahead of the curve.”

tags: marketing analytics tablets
From ‘Moneyball’ to Money Bombs: What Sports Analytics Can Teach Political Nerds – Rob Bluey – The Atlantic

“As many of my peers prepare for the trip to Austin, I have a story to share from Boston, where I attended the seventh annual MIT Sloan Sports Analytics Conference last weekend. I heard about the event from a Sports Illustrated story about the Houston Rockets, a team whose data-driven general manager, Daryl Morey, earned his MBA at Sloan.”

tags: analytics sports
Higher education on the move | Harvard Gazette

“When it comes to online education, the future is now. And it’s changing fast.”

tags: higher education education harvard

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Simple introduction to analytics

2013-03-07T21:30:50Z

This came up today in a discussion today, so I thought it would be useful to clarify some terminology related to analytics. Reporting and dashboards are not predictive analytics.

More generally,

Descriptive analytics is where you describe what is or has already happened, usually by processing a lot of data (which could be big). To show this, you use reporting or a dashboard that gives you tables, summaries, and graphics that make it easy to understand the situation and offers some insights that might not be obvious. The data might be last quarter’s sales information, movie theatre attendance, or e-book purchase preferences broken down by demographics, for example.
Predictive analytics uses techniques like simulation, statistics, and machine learning to extrapolate from past data or behavior to predict what might happen. Variations might be introduced so that you can get an idea of future results if you increase your sales force by 10%, decrease your price by 5%, or increase your manufacturing capacity, for example.
Prescriptive analytics often uses serious mathematical optimization techniques, simulation, and algorithms to help you understand how you should reach your goals. How many planes with given capacities, with crews based in specific locations, should be used on a given set of routes to accomodate so many passengers, all while minimizing fuel use and maximizing profits, for example.

By the way, be careful what you call analytics. If you compute the average sales attained by your staff last month this is probably just statistics and not deserving of the title “analytics.” I might be even less charitable and say it is just arithmetic.

Daily links for 03/07/2013

2013-03-07T16:30:18Z

The Evolution of Social Business: Six Stages of Social Business Transformation

“Companies are not created equal when it comes to social media maturity. In its latest research, Altimeter Group’s Charlene Li and Brian Solis uncovered a distinct gap between organizations that execute social media strategies and those that are truly a “social business.” On one side, there are businesses (specifically, departments) that are actively investing in social media without being tied to business goals. On the other side are organizations that are deeply integrating social media and social methodologies throughout the company to drive real business impact.”

tags: social business

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