[J111.Ebook] Ebook Lessons in Agile Management: On the Road to Kanban, by David J. Anderson

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David J. Anderson describes this collection as "The Missing Link in the Evolution of Kanban." Anderson developed the Kanban Method over years spent managing and coaching Agile development teams, at companies such as Sprint, Motorola and Microsoft, by integrating Lean thinking with Agile principles and practices. This compendium of anecdotes and epiphanies tells a very personal story as he shares his journey on the road to Kanban - now a popular method for improving predictability while managing change and risk in organizations worldwide.

This collection of over 150 articles compiled from the Agile Management blog and several other sources represents 12 years (1999-2011) of invaluable insights by David J. Anderson in managing software development. Each article has been carefully selected and grouped into one of 16 chapters on topics such as Leadership, Management, Peter Drucker, Theory of Constraints and Eli Goldratt, W. Edwards Deming, Human Resource Departments and Policies, Agile, Lean and Leading Change Initiatives. Each chapter is introduced with contemporary commentary explaining its relevance and contribution to both Agile and Kanban.

This book might have been titled, "The Very Best of Agile Management Blog" but that would do it an injustice. Each article has been lovingly reworked from the original to provide a coherent flowing story that introduces both the need for Kanban and how it emerged as a leading method for improving agility in knowledge work organizations. Many articles are enhanced with new observations and reflection on how the Agile community has progressed since original publication. In total there are around 20,000 words of current insights explaining why Kanban is necessary and what makes it an important innovation in the development of Agile methods.

"This is the book on leadership we've been waiting for." - Kurt H�usler

"David successfully blends the principles of flow, queues, theory of constraints, Lean, and Six Sigma to concoct a very powerful message that I have come to believe over the years: ‘You’ve got more capacity than you think!’” - Charan Atreya

• Sales Rank: #866076 in Books
• Brand: Brand: Blue Hole Press
• Published on: 2012-08-02
• Original language: English
• Number of items: 1
• Dimensions: 9.25" h x .96" w x 7.50" l, 1.63 pounds
• Binding: Paperback
• 426 pages

Features

• Used Book in Good Condition

About the Author
David J. Anderson is a thought leader in managing effective technology development. He leads a consulting, training and publishing business dedicated to developing, promoting and implementing sustainable evolutionary approaches for management of knowledge workers. He has 30 years experience in the high technology industry starting with computer games in the early 1980’s. He has led software teams delivering superior productivity and quality using innovative agile methods at large companies such as Sprint and Motorola. David is the author of two books, "Kanban – Successful Evolutionary Change for your Technology Business" and "Agile Management for Software Engineering – Applying the Theory of Constraints for Business Results". David is a founder of Lean-Kanban University, a business dedicated to assuring quality of training in Lean and Kanban throughout the world.

Most helpful customer reviews

3 of 3 people found the following review helpful.
"Numerous gems in the journey of a learning mind"
By Ellen Gottesdiener
David Anderson's latest book provides fascinating insight into the ongoing evolution of Kanban. David has collected his best writings, smartly categorized them, and provided retrospective comments on his thinking - including self-reflections on where and how his thinking changed.

I especially appreciate reading about David's influences. He is forthright about giving them credit--something that in itself is a form of leadership. Those influences include Taiichi Ohno (Toyota Production System) on muda, muri and mura; Eliyahu M. Goldratt on Theory of Constraints, specifically The Five Focusing Steps; John Seddon and Peter Senge on Systems Thinking; and W. Edwards Deming.

You'll find many memorable gems in this book about risk, leadership, estimating, trust, analysis, and of course flow. It's powerful for our Kanban, Lean, and Agile community to learn from the learning of its leaders.

3 of 3 people found the following review helpful.
Another classic, for sure...
By Adail Retamal
Having watched David steps since 2003, read all his books, and worked with him in Brazil in the pre- and post-Kanban era (we delivered the Zen of Agile Management workshop in 2008, and his first Kanban workshop in Brazil in 2010), I can only say that I highly recommend this book! The lessons and insights here are most valuable and will serve both newbies and experts alike. It is also a historical document, testifying about the maturation and evolution process that happened in the Agile community. Adapting TOC, Kanban, Lean and other production improvement techniques to knowledge work is definitely a major contribution by David to the management body of knowledge.

2 of 2 people found the following review helpful.
An fascinating read
By G. Cohen
David Anderson has been a tremendous influence on my thinking over the years, and he ranks in the top few authors whose writing is always a must read. He has done it again with "Lessons in Agile Management". His latest book brings together diverse bodies of knowledge from queuing theory, cycle times, and flow to the nature of knowledge work, leading knowledge workers and improving the effectiveness of teams. The book is a collection, with updates, of writings spanning nearly a decade. It catalogs Anderson's personal journey to tackle the challenges of large software development projects through what has become his Kanban change management method. Anderson synthesizes the works of W. Edward Deming's, Peter Drucker's Eli Goldratt, and others with his own analysis and insights on applying these theories to software development.

These is much to learn from Anderson's journey, and it is a gift that these lessons are available in a single book.

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[B836.Ebook] Free Ebook Big Data Analytics with Spark: A Practitioner's Guide to Using Spark for Large Scale Data Analysis, by Mohammed Guller

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Big Data Analytics with Spark is a step-by-step guide for learning Spark, which is an open-source fast and general-purpose cluster computing framework for large-scale data analysis. You will learn how to use Spark for different types of big data analytics projects, including batch, interactive, graph, and stream data analysis as well as machine learning. In addition, this book will help you become a much sought-after Spark expert.

Spark is one of the hottest Big Data technologies. The amount of data generated today by devices, applications and users is exploding. Therefore, there is a critical need for tools that can analyze large-scale data and unlock value from it. Spark is a powerful technology that meets that need. You can, for example, use Spark to perform low latency computations through the use of efficient caching and iterative algorithms; leverage the features of its shell for easy and interactive Data analysis; employ its fast batch processing and low latency features to process your real time data streams and so on. As a result, adoption of Spark is rapidly growing and is replacing Hadoop MapReduce as the technology of choice for big data analytics.

This book provides an introduction to Spark and related big-data technologies. It covers Spark core and its add-on libraries, including Spark SQL, Spark Streaming, GraphX, and MLlib. Big Data Analytics with Spark is therefore written for busy professionals who prefer learning a new technology from a consolidated source instead of spending countless hours on the Internet trying to pick bits and pieces from different sources.

The book also provides a chapter on Scala, the hottest functional programming language, and the program that underlies Spark. You’ll learn the basics of functional programming in Scala, so that you can write Spark applications in it.

What's more, Big Data Analytics with Spark provides an introduction to other big data technologies that are commonly used along with Spark, like Hive, Avro, Kafka and so on. So the book is self-sufficient; all the technologies that you need to know to use Spark are covered. The only thing that you are expected to know is programming in any language.

There is a critical shortage of people with big data expertise, so companies are willing to pay top dollar for people with skills in areas like Spark and Scala. So reading this book and absorbing its principles will provide a boost―possibly a big boost―to your career.

• Sales Rank: #201081 in Books
• Published on: 2015-11-25
• Released on: 2015-12-30
• Original language: English
• Number of items: 1
• Dimensions: 10.00" h x .69" w x 7.00" l, .0 pounds
• Binding: Paperback
• 277 pages

About the Author

Mohammed Guller is the principal architect at Glassbeam, where he leads the development of advanced and predictive analytics products. He is a big data and Spark expert. He is frequently invited to speak at big data–related conferences. He is passionate about building new products, big data analytics, and machine learning.

Over the last 20 years, Mohammed has successfully led the development of several innovative technology products from concept to release. Prior to joining Glassbeam, he was the founder of TrustRecs.com, which he started after working at IBM for five years. Before IBM, he worked in a number of hi-tech start-ups, leading new product development.

Mohammed has a master's of business administration from the University of California, Berkeley, and a master's of computer applications from RCC, Gujarat University, India.

Most helpful customer reviews

4 of 4 people found the following review helpful.
Good (but very basic) book. More breath than depth
By Abhishek Srivastava
I liked the book. it nice and simple and good for beginners.

One issue I found is that this book covers the the entire spark eco-system (spark core, spark sql, spark streaming, mllib) in a very brief way. it doesn't go deep into any of the topics. This makes it very similar to the spark programming guide on the web which also adopts a similar pattern.

What would have been nice if the author would have gone deep into spark-core. Upon reading this book, it didn't teach me anything more than the spark programming guide

5 of 6 people found the following review helpful.
If you want to learn Spark, buy this book. Highly recommended
By Ian Stirk
Hi,

I have written a detailed chapter-by-chapter review of this book on www DOT i-programmer DOT info, the first and last parts of this review are given here. For my review of all chapters, search i-programmer DOT info for STIRK together with the book's title.

This book aims to provide a “...concise and easy-to-understand tutorial for big data and Spark”. How does it fare?

Spark is increasing the tool of choice for big data processing, being much faster than Hadoop’s MapReduce. After putting Spark into a big data context, the book aims to cover Spark’s core library, together with its more specialized libraries for Streaming, Machine Learning, SQL, and Graphing.

The book is aimed at developers that are new to Spark, some general background programming knowledge required, but little else.

Chapter 1 Big Data Technology Landscape

This chapter opens with a discussion about the current big data age, with data as the lifeblood of organizations, and growing exponentially. The standard 3Vs definition of big data is explored (velocity, variety, volume). Traditional relational database management systems (RDBMS) are unable to process these large volumes in a timely manner – this is where the scalability of big data systems comes into its own.

Next, the chapter discusses some technologies that are either used with Spark, or Spark competes with. The first technology is Hadoop, this is fault tolerant and scalable, and runs on commodity hardware. The three major components of Hadoop are discussed: YARN (Yet Another Resource Negotiator), MapReduce (distributed processing model), and HDFS (Hadoop Distributed File System). Spark is increasingly being used in place of MapReduce owning to its faster speed. The section briefly discusses Hive, a data warehouse with a SQL like interface, Spark SQL is expected to supersede Hive on many systems.

The chapter continues with a look at some common binary formats for serializing (storing on disk) big data, and their pros and cons. Specifically Avro, Thrift, Protocol Buffers, and SequenceFile are examined. Next, some column storage formats, which have performance advantages when the client requires a subset of columns, were briefly discussed, namely: RCFile, ORC, and Parquet.

Then a brief overview of messaging systems is provided, together with the advantages of having a layer of abstraction between producers and consumers. Specifically, Kafka and ZeroMQ are discussed with the aid of useful supporting diagrams.

NoSQL is then examined. The various types of NoSQL databases have different aims to the traditional RDBMS, typically trading Atomicity, Consistency, Isolation, Durability (ACID) for scalability and flexibility. The specific NoSQL databases briefly discussed are Cassandra and HBase. I sometimes wonder if it is meaningful to group NoSQL databases together. Is it meaningful to divide sports into Football and NoFootball? Are all the NoFootball sports meaningful as a group?

The chapter ends with a look at some distributed SQL query engines, these do not use MapReduce batch jobs, and are thus more oriented to interactive querying. The engines briefly examined are: Impala, Presto, and Apache Drill.

This chapter provides an excellent overview of big data technology. It should be noted there are many more technologies than described, but the examples given are sufficient to explain the topic areas. This is possibly the best backgrounder to big data I’ve read.

The discussions are very well written, concise and clear, with helpful diagrams, and no wasted words. There’s a good flow between the topics, and useful links between chapters. There are website links for further information. These traits apply to all the chapters in the book.
.
.
.
Conclusion

This book aims to provide a “...concise and easy-to-understand tutorial for big data and Spark”, and clearly succeeds. The book is exceptionally well written. Helpful explanations, diagrams, practical step-by-step walkthroughs, annotated code, inter-chapter links, and website links abound throughout.

The book is aimed at developers that are new to Spark, and explains concepts from the beginning. If you work through the book you should become competent in the use of Spark, there is much more to learn of course, but this book gives a solid foundation in both core Spark and its major specialized libraries: Streaming, Machine Learning, SQL, and Graphing.

The book is based on workshops given by the author, and clearly the feedback from these has been useful in creating this book, since it seems to have answered all the questions I had.

This book provides everything you need to know to get started with Spark, explained in an easy-to-follow manner. If you want to learn Spark, buy this book. Highly recommended

2 of 2 people found the following review helpful.
Well Organized and informative book
By Technocrat
This book is a very well written definitive overview of Spark. This is a great book for those who want to learn about spark but dont know where to start from.
Fundamentals are very well explained in the book for developers who are new to spark. It starts with great overview of big data technology and helps in building basics and then moves on to explore more advanced topics. The book covers Spark core and its specialized add-on libraries too. This book also contains a plenty of sample examples which are really useful. Even if you are new to the subject this book has enough information to get a developer started on spark projects.
In short this book is really well organized, very informative and easy to follow. Highly recommended .

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• Sales Rank: #2530986 in eBooks
• Published on: 2012-07-30
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• Binding: Paperback
• 732 pages

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[J794.Ebook] Free Ebook Nuclear Energy Conversion, by Mohamed Mohamed El-Wakil

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• Sales Rank: #2184012 in Books
• Brand: Brand: Amer Nuclear Society
• Published on: 1982-06
• Original language: English
• Number of items: 1
• Dimensions: 9.25" h x 6.25" w x 1.50" l,
• Binding: Hardcover
• 666 pages

Features

• Used Book in Good Condition

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0 of 1 people found the following review helpful.
Five Stars
By Karam Nashwan
This is an awesome book

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Critical essays provide in-depth analysis of each character and comprehensive profiles discuss their key traits and other attributes. The protagonist of Fitzgerald's novel is closely associated with some of America's most prevalent obsessions: wealth, greed, and ambition.

• Sales Rank: #2799607 in Books
• Published on: 2004-02
• Original language: English
• Number of items: 1
• Dimensions: .47" h x 6.24" w x 9.22" l, 1.10 pounds
• Binding: Paperback
• 180 pages

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One Thing's Sure and Nothing's Surer, The Rich Get Richer and The Poor Get---Children!
By Sylviastel
Jay Gatsby is better known as the "Great Gatsby" from F. Scott Fitzgerald's novel of the same name. The novel, "The Great Gatsby," was the most definitive novel about roaring twenties and Jay Gatsby as a symbol of materialism. Harold Bloom's series of literary characters would be incomplete without mentioning Jay Gatsby.

If you want to know more about Fitzgerald's classic novel and his classic invention of Jay Gatsby, you will be interested to learn about other literary scholars views and analysis of him as well. The book includes a compilation of essays like "Fitzgerald's Brave New World," from Edwin Fussell; "The Great Gatsby: Finding a Hero," by Henry Dan Piper; "The Great Gatsby: Apogee of Fitzgerald's Mythopoeia," by Neila Seschachari; "The Great Gatsby," by Brian Way; "I Could Still Hear The Music: Jay Gatsby and the Musical Metaphor," by Bruce Brewer; "Money, Love, and Aspiration in 'The Great Gatsby,'" by Roger Lathbury; "Inventing Gatsby," by Richard Lehan; "The Great Narcissist: A Study of Fitzgerald's Jay Gatsby," by Giles Mitchell; "The Sexual Drama of Nick and Gatsby," by Edward Wasiolek; "Gatsby as Gangster," by Thomas H. Pauly; and "The Great Gatsby and the Good American LIfe," by Ronald Berman.

The book includes character profile, contributors, bibliography, index, analysis of character, editor's note and introduction too.

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