Agile Metrics in Action: A good how-to guide to getting better performance measurements – #programming #bookreview

Agile Metrics in Action

Christopher W. H. Davis


In the rapidly changing world of software development, metrics “represent the data you can get from your application lifecycle as it applies to the performance of software development teams,” Christopher W. H. Davis writes in his well-written, well-structured new book, Agile Metrics in Action.

“A metric can come from a single data source or it can be a combination of data from multiple data sources. Any data point that you track eventually becomes a metric that you can use to measure your team’s performance.”

The goals of agile metrics include collecting and analyzing data from almost every useful and accessible point in the software development life cycle, so team and individual performances can be measured and improved, and processes can be streamlined.

A key aspect of the data collection and analysis process is distributing the resulting information “across the organization in such a way that everyone can get the data they care about at a glance,” Davis says. He explains how and highlights some “traps” that teams can “fall into when they start publishing metrics,” such as “[s]ending all the data to all stakeholders,” many of whom won’t know what to do with most of it.

Metrics remain a controversial topic for many software developers, Davis emphasizes. So any business leader planning to rush his or her company into adopting agile metrics will need to proceed cautiously, instead. It is vital to get buy-in first from developers and their managers, he says.

“There will likely be people in your group who want nothing to do with measuring their work,” he explains. “Usually this stems from the fear of the unknown, fear of Big Brother, or a lack of control. The whole point here is that teams should measure themselves, not have some external person or system tell them what’s good and bad. And who doesn’t want to get better? No one is perfect—we all have a lot to learn and we can always improve.”

The concept of continuous development is a key topic in this book. “In today’s digital world consumers expect the software they interact with every day to continuously improve,” Davis states. “Mobile devices and web interfaces are ubiquitous and are evolving so rapidly that the average consumer of data expects interfaces to continually be updated and improved. To be able to provide your consumers the most competitive products, the development world has adapted by designing deployment systems that continuously integrate, test, and deploy changes. When used to their full potential, continuous practices allow development teams to hone their consumer’s experience multiple times per day.”

Of course, continuous development produces continuous data to measure and manage, as well, using agile metrics techniques.

Many different topics are addressed effectively in this book. And the practices the author presents are organized to work with any development process or tool stack. However, the software tools Davis favors for this book’s code-based examples include Grails, Groovy and MongoDB.

Agile Metrics in Action is structured and written to serve as a how-to book for virtually anyone associated with a software development team that relies on agile metrics. You may not understand all of the text. But if you take your time with this well-illustrated book, you can at least gain a better comprehension of what agile metrics means, how the process works, and why it is important to your employer, your group and your paycheck.

Si Dunn

R IN ACTION: Data Analysis and Graphics with R, 2nd Edition – #bookreview

R in Action

Data Analysis and Graphics with R

Robert I. Kabacoff

Manning – paperback

Whether data analysis is your field, your current major or your next career-change ambition, you likely should get this book. Free and open source  R is one of the world’s most popular languages for data analysis and visualization. And Robert I. Kabacoff’s updated new edition is, in my opinion, one of the top books out there for getting a handle on R. (I have used and previously reviewed several R how-to books.)

R is relatively easy to install on Windows, Mac OS X and Linux machines. But it is generally considered difficult to learn. Much of that is because of its rich abundance of features and packages, as well as its ability to create many types of graphs. “The base installation,” Kabacoff writes, “provides hundreds of data-management, statistical, and graphical functions out of the box. But some of its most powerful features come from the thousands of extensions (packages) provided by contributing authors.”

Kabacoff concedes: “It can be hard for new users to get a handle on what R is and what it can do.” And: “Even the most experienced R user is surprised to learn about features they were unaware of.”

R in Action, Second Edition, contains more than 200 pages of new material. And it is nicely structured to meet the needs of R beginners, as well as those of us who have some experience and want to gain more.

The book (579 pages in print format) is divided into five major parts. The first part, “Getting Started,” takes the beginner from an installing and trying R to creating data sets, working with graphs, and managing data. Part 2, “Basic Methods,”focuses on graphical and statistical techniques for obtaining basic information about data.”

Part 3, “Intermediate Methods,” moves the reader well beyond “describing the relationship between two variables.” It introduces  regression, analysis of variance, power analysis, intermediate graphs, and resampling statistics and bootstrapping. Part 4 presents “Advanced Methods,” including generalized linear models, principal components and factor analysis, time series, cluster analysis, classification, and advanced methods for missing data.

Part 5, meanwhile, offers how-to information for “Expanding Your Skills.” The topics include: advanced graphics with ggplot2, advanced programming, creating a package, creating dynamic reports, and developing advanced graphics with the lattice program.

A key strength of R in Action, Second Edition is Kabacoff’s use of generally short code examples to illustrate many of the ways that data can be entered, manipulated, analyzed and displayed in graphical form.

The first thing I did, however, was start at the very back of the book, Appendix G, and upgrade my existing version of R to 3.2.1, “World-Famous Astronaut.” The upgrade instructions could have been a little bit clearer, but after hitting a couple of unmentioned prompts and changing a couple of wrong choices, the process turned out to be quick and smooth.

Then I started reading chapters and keying in some of the code examples. I had not used R much recently, so it was fun again to enter some commands and numbers and have nicely formatted graphs suddenly pop open on the screen.

Even better, it is nice to have a LOT of new things to learn, with a well-written, well-illustrated guidebook in hand.

Si Dunn


D3.js in Action: A good book packed with data visualization how-to info – #javascript #programming

D3.js in Action

Elijah Meeks

Manning – paperback


The D3.js library is very powerful, and it is full of useful choices and possibilities. But, you should not try to tackle Elijah Meeks’s new book if you are a JavaScript newcomer and not also comfortable with HTML, CSS and JSON.

It likewise helps to understand how CSVs (Comma Separated Values) can be used. And you should know how to set up and run local web servers on your computer. Prior knowledge of D3.js and SVG (Scalable Vector Graphics) is not necessary, however.

Some reviewers have remarked on the amount of how-to and technical information packed into DS3.js in Action. It is indeed impressive. And, yes, it really can seem like concepts, details and examples are being squirted at you from a fire hose, particularly if you are attempting to race through the text. As Elijah Meeks writes, “[T]he focus of this book is on a more exhaustive explanation of key principles of the library.”

So plan to take your time. Tackle D3.js in small bites, using the website and this text. I am pretty new to learning data visualization, and I definitely had never heard of visualizations such as Voronoi diagrams, nor tools such as TopoJSON, until I started working my way through this book. And those are just a few of the available possibilities.

I have not yet tried all of the code examples. But the ones I have tested have worked very well, and they have gotten me thinking about how I can adapt them to use in some of my work.

I am a bit disappointed that the book takes 40 pages to get to the requisite “Hello, world” examples. And once you arrive, the explanations likely will seem a bit murky and incomplete to some readers.

However, that is a minor complaint. D3.js in Action will get frequent use as I dig deeper into data visualization. D3.js and Elijah Meeks’s new book are keepers for the long-term in the big world of JavaScript.

Si Dunn