Maker City: How to reinvigorate local economies and cultures – #bookreview

Reinventing a city does not have to start from the top down.  You don’t need big government initiatives and huge funding, this noteworthy book contends.

People within America’s growing “Maker culture” can rework and improve a local economy. They can bring needed and worthwhile changes to a city’s culture using significantly smaller budgets and much less government intervention. And the reinvigoration can happen in small, rural towns as well as in large metropolitan areas, the authors of Maker City believe.

What, exactly, is Maker culture? Here’s how it is defined in this book:

“Today’s Makers are crafters, artists and artisans, technologists, hobbyists, amateur scientists, entrepreneurs, engineers, woodworkers, roboticists, and many others. They are young people engaging in hands-on projects that introduce them to science and technology in creative ways. Makers are also adults who see themselves as inventors and experimentalists. Some have PhDs and others are self-educated. Makers are practicing a craft or challenging themselves to learn a new hobby. They are creative problem-solvers who gain the confidence that they can tackle ever-larger problems.”

The movement brings the local “best and brightest” together with other Makers around the globe, linked together via the Internet or in person as solutions to problems are sought, made and tested.

A key tenet of city-level Maker culture is “Open Innovation, the idea that the best solutions do not lie with any one individual or institution inside city government but must be created through collaboration and engagement that looks outside for answers and examples of what to do to affect change.”

The notion of city reinvention typically puts spotlights on big cities where factories and industries have been lost and large buildings and neighborhoods have fallen into ruin. For example, efforts to find a major new role, such as commercial shipyard, for the old Brooklyn Navy Yard repeatedly failed, until a new, Maker-oriented approach was tried. That’s when the Brooklyn Navy Yard “started to make a comeback as a community housing many smaller businesses made up of Makers, artists, artisans, and manufacturing concerns. Today over 330 businesses and 7,000 people work out of the Brooklyn Navy Yard in 3.5 million square feet growing to 5.0 million square feet by 2018,” Maker City reports.

Small towns also can benefit from Maker innovation and talent, the book emphasizes. Ways can be found to take advantage of local history and draw visitors, as well as new residents. Old, unused buildings can be upgraded to emphasize and celebrate local history and serve as meeting centers or performance sites. Other buildings can be converted to innovation centers and incubators that give local residents places or other help to start businesses and hire other local residents.

The book is well-written and well-organized and offers a wide range of ideas, case studies and trend reports. For example, big assembly line jobs are not coming back, unless robots provide the “labor.” But small-scale manufacturing is expanding, thanks to 3D printers and other devices and innovations. Small-scale manufacturers also are often selling their products directly to customers from their sites. And customers are showing a stronger preference for buying locally made products.

Whether you work in business, government, science or education or are simply concerned about urban renewal, Maker City deserves careful consideration.

Si Dunn

Maker City

A Practical Guide for Reinventing Our Cities

Peter Hirshberg, Dale Dougherty, Marcia Kadanoff

Maker Media, paperback, Kindle

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‘Introducing Data Science’ – A good doorway into the world of processing, analyzing & displaying Big Data – #bookreview

Introducing Data Science

Davy Cielen, Arno D. B. Meysman, and Mohamed Ali

Manning – paperback

The three authors of this book note that “[d]ata science is a very wide field, so wide indeed that a book ten times the size of this one wouldn’t be able to cover it all. For each chapter, we picked a different aspect we find interesting. Some hard decisions had to be made to keep this book from collapsing your bookshelf!”

In their decisions and selections, they have made some good choices. Introducing Data Science is well written and generally well-organized (unless you are overly impatient to get to hands-on tasks).

The book appears to be aimed primarily at individual computer users and persons contemplating possible careers in data science–not those already working in, or heading, big data centers. The book also could be good for managers and others trying to wrap their heads around some data science techniques that could help them cope with swelling mountains of business data.

With this book in hand, you may be impatient to open it to the first chapter and dive headfirst into slicing, dicing, and graphing data. Try to curb your enthusiasm for a little while. Books from Manning generally avoid the “jump in now, swim later” approach. Instead, you get some overviews, explanations and theory first. Then you start getting to the heart of the matter. Some like this approach, while others get impatient with it.

In Introducing Data Science, your “First steps in big data” start happening in chapter five, after you’ve first delved into the data science process: 1. Setting the research goal; 2. Retrieving data; 3. Data preparation, 4. Data exploration; 5. Data modeling; and 6. Presentation and automation.

The “First steps” chapter also is preceded by chapters on machine learning and how to handle large data files on a single computer.

Once you get to Chapter 5, however, your “First steps” start moving pretty quickly. You are shown how to work (at the sandbox level) with two big data applications, Hadoop and Spark. And you get examples of how even Python can be used to write big data jobs.

From there, you march on to (1) the use of NoSQL databases and graph databases, (2) text mining and text analytics, and (3) data visualization and creating a small data science application.

It should be noted and emphasized, however, that the concluding pages of chapter 1 do present “An introductory working example of Hadoop.” The authors explain how to run “a small [Hadoop] application in a big data context,” using a Hortonworks Sandbox image inside a VirtualBox.

It’s not grand, but it is a start in a book that otherwise would take four chapters to get to the first hands-on part.

Near the beginning of their book, the authors also include a worthy quote from Morpheus in “The Matrix”: “I can only show you the door. You’re the one that has to walk through it.”

This book can be a good entry door to the huge and rapidly changing field of data science,  if you are willing to go through it and do the work it presents.

Si Dunn

Will “Smart” Device Dependence Make You Increasingly Dumb?

I strolled into my favorite Austin Starbucks recently and noticed a startling sight. Every person standing in line or sitting at tables simultaneously had their head down as if in group prayer. All at the same moment were staring at their smartphones.

I pulled out my own phone, dramatically flipped it open, held it aloft, and waved it in silent protest. No one got the joke, because no one noticed.

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We’ve all seen people become panic-stricken and helpless when they realize they have lost or forgotten their “smart” device, or had it stolen. “Everything—my whole life—is on there!” one friend wailed recently. “All my pictures, my personal information, my contacts. And—oh, god–work emails! I don’t know what to do!” She kept frantically digging through her big purse, which also contained “everything,” including papers from work, so she could keep working at home after she got off work. When I called her phone from my phone, we found her “smart” phone buried deep beneath makeup containers and assorted other purse rubble.

Many people now use their smartphones for “everything,” from paying a restaurant check (after using the calculator function to split it and calculate the tip) to hailing an Uber ride and remotely controlling their home air conditioning. And, anytime a question is raised in a group, several people will circumvent natural debate or brainstorming by immediately going to Google and reading off some article titles and paragraphs.

Meanwhile, a few unrelated videos also will pop up and be shared:  Cat attacks python! Man sets shoes on fire by standing on hot coals! Ha-ha-ha!

The smartphone video distractions are only going to get worse. As AT&T’s CEO, Randall Stephenson recently told Fortune magazine: “…mobile video…is the real deal,” adding: “Half our mobile network traffic is video now, and it’s really growing fast.”

So, recent statutes banning talking or texting on a digital device while driving are now far behind the curve of progress. (“Sorry, officer, I was not breaking the law. I was watching Game of Thrones while paying no attention to the traffic and scenery around me.”)

Perhaps it is time to ask yourself two serious questions. Are you losing touch with the real world as you become increasingly distracted by your smartphone? And will your growing dependence on its “smart”-ness make you correspondingly “dumb” over time?

Si Dunn

BIG DATA: A well-written look at principles & best practices of scalable real-time data systems – #bookreview

 

 

Big Data

Principles and best practices of scalable real-time data systems

Nathan Marz, with James Warren

Manning – paperback

Get this book, whether you are new to working with Big Data or now an old hand at dealing with Big Data’s seemingly never-ending (and steadily expanding) complexities.

You may not agree with all that the authors offer or contend in this well-written “theory” text. But Nathan Marz’s Lambda Architecture is well worth serious consideration, especially if you are now trying to come up with more reliable and more efficient approaches to processing and mining Big Data. The writers’ explanations of some of the power, problems, and possibilities of Big Data are among the clearest and best I have read.

“More than 30,000 gigabytes of data are generated every second, and the rate of data creation is only accelerating,” Marz and Warren point out.

Thus, previous “solutions” for working with Big Data are now getting overwhelmed, not only by the sheer volume of information pouring in but by greater system complexities and failures of overworked hardware that now plague many outmoded systems.

The authors have structured their book to show “how to approach building a solution to any Big Data problem. The principles you’ll learn hold true regardless of the tooling in the current landscape, and you can use these principles to rigorously choose what tools are appropriate for your application.” In other words, they write, you will “learn how to fish, not just how to use a particular fishing rod.”

Marz’s Lambda Architecture also is at the heart of Big Data, the book. It is, the two authors explain, “an architecture that takes advantage of clustered hardware along with new tools designed specifically to capture and analyze web-scale data. It describes a scalable, easy-to-understand approach to Big Data systems that can be built and run by a small team.”

The Lambda Architecture has three layers: the batch layer, the serving layer, and the speed layer.

Not surprisingly, the book likewise is divided into three parts, each focusing on one of the layers:

  • In Part 1, chapters 4 through 9 deal with various aspects of the batch layer, such as building a batch layer from end to end and implementing an example batch layer.
  • Part 2 has two chapters that zero in on the serving layer. “The serving layer consists of databases that index and serve the results of the batch layer,” the writers explain. “Part 2 is short because databases that don’t require random writes are extraordinarily simple.”
  • In Part 3, chapters 12 through 17 explore and explain the Lambda Architecture’s speed layer, which “compensates for the high latency of the batch layer to enable up-to-date results for queries.”

Marz and Warren contend that “[t]he benefits of data systems built using the Lambda Architecture go beyond just scaling. Because your system will be able to handle much larger amounts of data, you’ll be able to collect even more data and get more value out of it. Increasing the amount and types of data you store will lead to more opportunities to mine your data, produce analytics, and build new applications.”

This book requires no previous experience with large-scale data analysis, nor with NoSQL tools. However, it helps to be somewhat familiar with traditional databases. Nathan Marz is the creator of Apache Storm and originator of the Lambda Architecture. James Warren is an analytics architect with a background in machine learning and scientific computing.

If you think the Big Data world already is too much with us, just stick around a while. Soon, it may involve almost every aspect of our lives.

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 d3js.org 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

SOFT SKILLS: A very useful ‘life manual’ for software developers – #programming #bookreview

Soft Skills

The Software Developer’s Life Manual

John Z. Sonmez

Manning paperback

I really wish I had had this book when I started a 14-year career in software development and testing. I was hired back in the days when you could get a software job by having a college degree (in anything), a couple of positive references and some decent writing skills. If you could also turn on a computer and bring up the DOS prompt, so much the better.

No matter how many skills you actually had, you were going to spend a couple of months learning your new environment and your new job, while also attending free, company-sponsored training classes (during working hours). Meanwhile, if you had any questions, you could just go ask the C guru down the hall or dour Mister Assembler, who lived in the big, corner cubicle and seemed to have no other life.

I am retired now from the corporate world of software. And when, out of curiosity, I look at today’s help-wanted postings for developers and testers, I am stunned by how much knowledge, training and verifiable skills one person is expected to bring to the table. At least ten jobs, it seems, have been rolled into one.

For that reason and more, I highly recommend Soft Skills by John Z. Sonmez. He believes, he says, in taking “a holistic approach to software development. This means that I think that if you want to be a better software developer—a better anything, really—you need to focus on the entire person, not just one or two areas of your life.”

Sonmez offers up a wealth of how-to information and useful advice covering everything from “hacking” a job interview to developing a personal brand and staying physically fit in a job that requires long hours sitting on one’s butt. He also offers tips for learning new things quickly, staying productive (using a modified version of the Pomodoro Technique)–and investing part of your paycheck so you can retire early or at least have a comfortable cushion if you get laid off and decide to become an independent consultant.

Yes, there is a lot of common advice sense in Soft Skills–the kind of advice you likely have heard before but ignored. Still, Sonmez’s book makes clear, compelling cases for why you really do have to watch out for–and take care of–yourself these days. You seemingly can’t count on an employer to do much of anything anymore, except view you as a unit of cost to be reduced or eliminated as soon as possible.

“Most software developers starting out in their careers make a few huge mistakes,” Sonmez writes. “The biggest of those mistakes, by far, is not treating their software development career as a business. Don’t be fooled; when you set out into the world to write code for a living, you’re no different than the blacksmith of old times setting up shop in a medieval town. Times may have changed, and most of us work for a company, but our skills and our trade belong to us and we can always choose to set up shop somewhere else. This kind of mindset is crucial to managing your career, because when you start to think of yourself as a business, you start to make good business decisions.”

This is a mindset I wish I had acquired and expanded when I got my first job in software and then began to surf the periodic waves of layoffs. If you are new at working in software development or still trying to get your foot in the door, you can get some very good information and guidance from this book. The same goes if your career currently is floundering and needs a reboot. Don’t just hit CTRL-ALT-DEL and go storming out the door. Try reading some of Sonmez’s chapters first–and at least have your resume reworked by experts who can help you boost your personal “brand.”

Si Dunn

 

Cloudera Administration Handbook – How to become an effective Big Data administrator of large Hadoop clusters – #bookreview

 

 

Cloudera Administration Handbook

 Rohit Menon

Packt PublishingKindle, paperback

 

The explosive growth and use of Big Data in business, government, science and other arenas has fueled a strong demand for new Hadoop administrators. The administrators’ key duty is to set up and maintain Hadoop clusters that help process and analyze massive amounts of information.

New Hadoop administrators and those looking to join their ranks especially will want to give good consideration to The Cloudera Administration Handbook by Rohit Menon. This is a well-organized, well-written and solidly illustrated guide to building and maintaining large Apache Hadoop clusters using Cloudera Manager and CDH5.

The author has an extensive computer science background and is a Cloudera Certified Apache Hadoop Developer. He notes that “Cloudera Inc., is a Palo Alto-based American enterprise software company that provides Apache Hadoop-based software, support and services, and training to data-driven enterprises. It is often referred to as the commercial Hadoop company.”

CDH, Menon points out, is the easy shorthand name for a rather awkward software title: “Cloudera’s Distribution Including Apache Hadoop.” CDH is “an enterprise-level distribution including Apache Hadoop and several components of its ecosystem such as Apache Hive, Apache Avro, HBase, and many more. CDH is 100 percent open source,” Menon writes.

The Cloudera Manager, meanwhile, “is a web-browser-based administration tool to manage Apache Hadoop clusters. It is the centralized command center to operate the entire cluster from a single interface. Using Cloudera Manager, the administrator gets visibility for each and every component in the cluster.”

The Cloudera Manager is not explored until nearly halfway into the book, and some may wish it had been explained sooner, since they may be trying to learn it on day one of their new job. However, Menon wants readers first to become familiar with “all the steps and operations needed to set up a cluster via the command line” at a terminal. And these are, of course, important considerations to becoming an effective, knowledgeable and versatile Hadoop Administrator.  (You may not always have access to Cloudera Manager while setting up or troubleshooting a cluster.)

The book’s nine chapters show its well-focused range:

  • Chapter 1: Getting Started with Apache Hadoop
  • Chapter 2: HDFS and MapReduce
  • Chapter 3: Cloudera’s Distribution Including Apache Hadoop
  • Chapter 4: Exploring HDFS Federation and Its High Availability
  • Chapter 5: Using Cloudera Manager
  • Chapter 6: Implementing Security Using Kerberos
  • Chapter 7: Managing an Apache Hadoop Cluster
  • Chapter 8: Cluster Monitoring Using Events and Alerts
  • Chapter 9: Configuring Backups

You will have to bring some hardware and software experience and skills to the table, of course. Apache Hadoop primarily is run on Linux. “So having good Linux skills such as monitoring, troubleshooting, configuration, and security is a must” for a Hadoop administrator, Menon points out. Another requirement is being able to work comfortably with the Java Virtual Machine (JVM) and understand Java exceptions.

But those skills and his Cloudera Administration Handbook can take you from “the very basics of Hadoop” to taking up “the responsibilities of a Hadoop administrator and…managing huge Hadoop clusters.”

Si Dunn

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