Mike Loukides

Mike Loukides is Vice President of Content Strategy for O'Reilly Media, Inc. He's edited many highly regarded books on technical subjects that don't involve Windows programming. He's particularly interested in programming languages, Unix and what passes for Unix these days, and system and network administration. Mike is the author of System Performance Tuning", and a coauthor of "Unix Power Tools." Most recently, he's been fooling around with data and data analysis, languages like R, Mathematica, and Octave, and thinking about how to make books social.

Data Science for Business

What business leaders need to know about data and data analysis to drive their businesses forward.

DataScienceForBusinessCoverA couple of years ago, Claudia Perlich introduced me to Foster Provost, her PhD adviser. Foster showed me the book he was writing with Tom Fawcett, and using in his teaching at NYU.

Foster and Tom have a long history of applying data to practical business problems. Their book, which evolved into Data Science for Business, was different from all the other data science books I’ve seen. It wasn’t about tools: Hadoop and R are scarcely mentioned, if at all. It wasn’t about coding: business students don’t need to learn how to implement machine learning algorithms in Python. It is about business: specifically, it’s about the data analytic thinking that business people need to work with data effectively.

Data analytic thinking means knowing what questions to ask, how to ask those questions, and whether the answers you get make sense. Business leaders don’t (and shouldn’t) do the data analysis themselves. But in this data-driven age, it’s critically important for business leaders to understand how to work with the data scientists on their teams. Read more…

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Really Understanding Computation

Tom Stuart's new book will shed light on what you're really doing when you're programming.

It’s great to see that Tom Stuart’s Understanding Computation has made it out. I’ve been excited about this book ever since we signed it.

Understanding Computation started from Tom’s talk Programming with Nothing, which he presented at Ruby Manor in 2011. That talk was a tour-de-force: it showed how to implement a more-or-less complete programming system without using any libraries, methods, classes, objects, or even control structures, assignments, arrays, strings, or numbers. It was, literally, programming with nothing. And it was an eye-opener.

Shortly after I saw the conference video, I talked to Tom to ask if we could do more like this. And amazingly, the answer was “yes.” He was very interested in teaching the theory of computing through Ruby, using similar techniques. What does a program mean? What does it mean for something to be a program? How do we build languages that can handle ever more flexible abstractions? What kinds of problems can’t we solve computationally? It’s all here, and it’s all clearly demonstrated via Ruby code. It’s not code that you’d ever use in a real application (trust me, doing arithmetic without numbers, assignments, and control statements is ridiculously slow). But it is code that will expand your mind and leave you with a much better understanding of what you’re doing when you’re programming.
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Burning the Silos

The boundaries created by traditional management are just getting in the way of reducing product cycle times.

If I’ve seen any theme come up repeatedly over the past year, it’s getting product cycle times down. It’s not the sexiest or most interesting theme, but it’s everywhere: if it’s not on the front burner, it’s always simmering in the background.

Cutting product cycles to the bare minimum is one of the main themes of the Velocity Conference and the DevOps movement, where integration between developers and operations, along with practices like continuous deployment, allows web-native companies like Yahoo! to release upgrades to their web products many times a day. It’s no secret that many traditional enterprises are looking at this model, trying to determine what they can use or implement. Indeed, this is central to their long-term survival; companies as different from Facebook as GE and Ford are learning that they will need to become as agile and nimble as their web-native counterparts.

Integrating development and operations isn’t the only way to shorten product cycles. In his talk at Google IO, Braden Kowitz talked about shortening the design cycle: rather than build big, complete products that take a lot of time and money, start with something very simple and test it, then iterate quickly. This approach lets you generate and test lots of ideas, but be quick to throw away the ones that aren’t working. Rather than designing an Edsel, just to fail when the product is released, the shorter cycles that come from integrating product design with product development let you build iteratively, getting immediate feedback on what works and what doesn’t. To work like this, you need to break down the silos that separate engineers and designers; you need to integrate designers into the product team as early as possible, rather than at the last minute.

Data scientist DJ Patil makes a similar point in Building Data Science Teams. Data isn’t new, nor is data analysis. Our ability to collect data by the petabyte certainly is new, but it isn’t revolutionary in itself. What really characterizes data science is the way data is incorporated into the product development cycle. Data analysts are frustrated and ineffective when they live in silos, and all they do is design complex queries and generate reports. They need to be integrated into decision making and product design. A data group that’s isolated from the organization’s business isn’t going to have the understanding they need to create insights from data. Their role will be limited to confirming what some manager or other thinks, and that’s neither fulfilling or effective.
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Faster and stronger: Looking back on Velocity 2012

Faster and stronger: Looking back on Velocity 2012

Abstraction problems, resilience engineering and outliers among Velocity's big themes.

Mike Loukides highlights talks from Velocity 2012, including: Bryan McQuade on the importance of understanding the full stack, Dr. Richard Cook on failures and complex systems, Mike Christian on redundant data centers, and John Rauser on the value of outliers.

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Velocity 2011 retrospective

Velocity 2011 retrospective

Resilience engineering and data's role in performance are key trends in web ops.

A number of emerging themes are defining the web operations world, including: resilience engineering, new approaches to failure, and the role data plays in boosting performance.

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Why OSCON Java?

Why OSCON Java?

OSCON Java will look at the language's role in data, mobile, enterprise, and cloud computing.

The Java community has always been a broad, fractious, interesting mess, capable of doing surprising things with little warning, and that's precisely why we're attracted to it.

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Velocity 2011

Velocity 2011

A tribe of web performance and operations pros is pushing the web forward.

As we approach the fourth Velocity conference, here's a look at how the web performance and operations communities came together, what they've done to improve the web experience, and the work that lies ahead.

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