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Disruptive Possibilities: How Big Data Changes Everything [Kindle Edition]

Jeffrey Needham

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Big data has more disruptive potential than any information technology developed in the past 40 years. As author Jeffrey Needham points out in this revealing book, big data can provide unprecedented visibility into the operational efficiency of enterprises and agencies.

Disruptive Possibilities provides an historically-informed overview through a wide range of topics, from the evolution of commodity supercomputing and the simplicity of big data technology, to the ways conventional clouds differ from Hadoop analytics clouds. This relentlessly innovative form of computing will soon become standard practice for organizations of any size attempting to derive insight from the tsunami of data engulfing them.

Replacing legacy silos—whether they’re infrastructure, organizational, or vendor silos—with a platform-centric perspective is just one of the big stories of big data. To reap maximum value from the myriad forms of data, organizations and vendors will have to adopt highly collaborative habits and methodologies.

Über den Autor und weitere Mitwirkende

Jeff Needham is the founder of Scale Abilities, Inc., a Silicon Valley consulting firm, and does ecosystem platform engineering at Hortonworks in Palo Alto, California. With 25 years experience in both hardware and software engineering, he is a frequent writer and speaker on topics of database performance and scalability, platform engineering and Hadoop cluster technology. Customers appreciate Jeff's creative strategies for evaluating and implementing their big data initiatives.


  • Format: Kindle Edition
  • Dateigröße: 1969 KB
  • Seitenzahl der Print-Ausgabe: 90 Seiten
  • Gleichzeitige Verwendung von Geräten: Keine Einschränkung
  • Verlag: O'Reilly Media; Auflage: 1 (6. Mai 2013)
  • Verkauf durch: Amazon Media EU S.à r.l.
  • Sprache: Englisch
  • ASIN: B00CLH387W
  • Text-to-Speech (Vorlesemodus): Aktiviert
  • X-Ray:
  • Word Wise: Nicht aktiviert
  • Amazon Bestseller-Rang: #5.104 Kostenfrei in Kindle-Shop (Siehe Top 100 - Kostenfrei in Kindle-Shop)

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Die hilfreichsten Kundenrezensionen auf (beta) 4.2 von 5 Sternen  28 Rezensionen
2 von 2 Kunden fanden die folgende Rezension hilfreich
3.0 von 5 Sternen not quite what I thought 6. Dezember 2013
Von Josh Denesnah - Veröffentlicht auf
Format:Kindle Edition|Verifizierter Kauf
This was helpful to give me context on big data, the history, and some vision to the future. For good or ill, I expected more about how to think about introducing big data into my company.
2 von 2 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen want the real story on Hadoop - start here 16. Juli 2013
Von Amazon Customer - Veröffentlicht auf
Format:Kindle Edition|Verifizierter Kauf
If you want to get the down low on Hadoop from someone who has implemented it in the past and happens to be a** deep in it today then take a look at this candid short read from someone who knows what they are talking about from real life experience. This is a great place for people to get their head around the fact that Hadoop was developed to save money and that much of what is known today about how a data center is run can be challenged if not totally discarded in the context of Hadoop. how do you think they are running the website you are using right now?
2 von 2 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen Great Book... Will be interesting to read in a few years 10. Juni 2013
Von Jim Walker - Veröffentlicht auf
Format:Kindle Edition|Verifizierter Kauf
note to reader: set a reminder in a few years to read this again. i will bet we will be amazed by what jeff says here and how dead on he is.
2 von 2 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen Viewing the Internet as a Large-scale Computing Platform 7. Juni 2013
Von Here Now - Veröffentlicht auf
Format:Kindle Edition
As an author Jeffrey Needham manages in his short book the impressive feat of being sharply concise, broadly relevant, entertaining, personally committed and revealing in unfolding the aspects of his topic. He gives you just the history you need to understand the fundamental challenge of scale in the Big Data era of network computing. And the disruption in the book's title comes from the urgent insight that any organization that intends to take on the challenges of working with an internet-scale data set must adopt a platform engineering outlook, requiring all enterprise computing subject area experts to design specific pieces of the system with an awareness of what the system currently does and will evolve to do as a whole. Perpetual innovation from a platform view is the mantra this book will bring to scrum whiteboards, executive suites, and boardrooms.
2 von 2 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen Well worth reading... 15. Mai 2013
Von boulder_cons - Veröffentlicht auf
Format:Kindle Edition|Verifizierter Kauf
If you are in enterprise and business computing, you are surely aware that Big Data is a huge these days. It is huge not only in the amount of attention it gets, but also in the amount of the material it encompasses - it is easy to get lost in a lot of books written about Hadoop ecosystem and you can read tens of books just on this topic. And there is a lot of the relevant history of what came before, namely scientific computing, parallel and grid computing. We also need a way to see forest from the trees and piecing together big picture from its pieces is not an easy exercise.

Do yourself a favor and read this book - it is concise read that would help you understand big picture of what is different in Big Data versus software you are used to deploy. Author puts together wealth of advise helping you understand how technology, history, organizational politics and silo landscape would impact your Big Data projects. It would help you understand how we got where we are, and it would show you how companies that succeeded in the Big Data are doing it.

That is where disruption starts - current silo mentality many enterprises have is not well matched with Big Data, and author makes strong case that Big Data would require platform thinking above silo thinking, as well as a case for what would be impact in the larger impact on world around us. If you are in the process of implementing Big Data, or simply interested in future impact of Big Data, this book is worth a read.

There is also value for the specific audiences:

1. If you are interested about future, author is very experienced and knowledgable in Big Data space. While opinions about future are always subject to discussion, this is informed opinion from expert in the field that you should be familiar with.
2. If you are an engineer working on piece of the Big Data system, this book helps you understand platform engineering and background needed for platform engineers.
3. Finally, I think that author has life story worth sharing
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