Tricks of the Trade,"Turning Numbers into Knowledge", info for the new wave of Data Analysts

I just received from amazon.com Jonathan Koomey's Turning Numbers into Knowledge book, and one of the things that caught my eye is the Foreword where

There is nothing else like this book out there.
Nobody who deals with problems where numbers matter—and everybody in today’s world really needs to—should be without it.
John P. Holdren*
Woods Hole, MA, October 2007

And Professor Holdren explains the "Tricks of the Trade" course he taught at UC Berkeley.

Berkeley’s guardians of academic respectability eventually made me change what they regarded as too frivolous a title for the course to “Professional Methods for Interdisciplinary Careers”, but the focus remained the same for the 15+ years that I taught it. It covered ways of thinking through complex problems; how to find and manage information; how to function in a committee; how to identify and avoid common pitfalls in the interpretation of data; how to present results clearly in words, graphs, and tables; how to manage one’s time; and even how to avoid jet lag.

Many students over the years suggested that I should write a book teaching the “Tricks of the Trade”. Notwithstanding my advice to others about time management, however, I never found the time to write it.

With the 2001 publication of the first edition of Jonathan Koomey’s remarkable book, Turning Numbers into Knowledge, I realized that I no longer needed to try. Dr. Koomey, who had taken my course in the 1980s as a Berkeley graduate student, had plenty of ideas of his own about the need and how to fill it. And the book that he wrote surpassed what I would have done, if I had found the time, in every important respect

WSJ has a post on how there is a new wave of Business Schools planning to educate students in data analysis.

Business Schools Plan Leap Into Data

By MELISSA KORN And SHARA TIBKEN

Faced with an increasing stream of data from the Web and other electronic sources, many companies are seeking managers who can make sense of the numbers through the growing practice of data analytics, also known as business intelligence. Finding qualified candidates has proven difficult, but business schools hope to fill the talent gap.

This fall several schools, including Fordham University's Graduate School of Business and Indiana University's Kelley School of Business, are unveiling analytics electives, certificates and degree programs; other courses and programs were launched in the previous school year.

Some of the students who are thinking of getting into Data Analytics should consider Jonathan Koomey's book, Turning Numbers into Knowledge.

One way to look at Green Data Center Start-ups are they founded by engineers and scientists or VCs

Two of my cloud computing engineering friends and I are having a blast working on a technology solution that can be used in data centers as well as many other areas. I ran across Steve Blank's post on

How Scientists and Engineers Got It Right, and VC’s Got It Wrong

There are many parts of Steve's post that resonate with our team.

Startups are not smaller versions of large companies. Large companies execute known business models. In the real world a startup is about the search for a business model or more accurately, startups are a temporary organization designed to search for a scalable and repeatable business model.

...

Scientists and engineers as founders and startup CEOs is one of the least celebrated contributions of Silicon Valley.

It might be its most important.

We all worked in Silicon Valley, so we have a bunch of methods ingrained our thinking.

Why It’s “Silicon” Valley
In 1956 entrepreneurship as we know it would change forever.  At the time it didn’t appear earthshaking or momentous. Shockley Semiconductor Laboratory, the first semiconductor company in the valley, set up shop in Mountain View. Fifteen months later eight of Shockley’s employees (three physicists, an electrical engineer, an industrial engineer, a mechanical engineer, a metallurgist and a physical chemist) founded Fairchild Semiconductor.  (Every chip company in Silicon Valley can trace their lineage from Fairchild.)

The history of Fairchild was one of applied experimentation. It wasn’t pure research, but rather a culture of taking sufficient risks to get to market. It was learning, discovery, iteration and execution.  The goal was commercial products, but as scientists and engineers the company’s founders realized that at times the cost of experimentationwas failure. And just as they don’t punish failure in a research lab, they didn’t fire scientists whose experiments didn’t work. Instead the company built a culture where when you hit a wall, you backed up and tried a different path. (In 21^st century parlance we say that innovation in the early semiconductor business was all about “pivoting” while aiming for salable products.)

The Fairchild approach would shape Silicon Valley’s entrepreneurial ethos: In startups, failure was treated as experience (until you ran out of money.)

Conveniently, our idea does not need VC money or MBAs.

Scientists and Engineers = Innovation and Entrepreneurship
Yet when venture capital got involved they brought all the processes to administer existing companies they learned in business school – how to write a business plan, accounting, organizational behavior, managerial skills, marketing, operations, etc. This set up a conflict with the learning, discovery and experimentation style of the original valley founders.

Yet because of the Golden Rule, the VC’s got to set how startups were built and managed (those who have the gold set the rules.)

I have been reading Steve Blank and some of his ideas as he experiments with business models.

Earlier this year we developed a class in the Stanford Technology Ventures Program, (the entrepreneurship center at Stanford’s School of Engineering), to provide scientists and engineers just those tools – how to think about all the parts of building a business, not just the product. The Stanford class introduced the first management tools for entrepreneurs built around the business model / customer development / agile development solution stack. (You can read about the class here.)

Some of the best data center conversations I have are on new business models not technology. Give it a try sometime.  It is much more fun.