Big Data For Dummies und über 1,5 Millionen weitere Bücher verfügbar für Amazon Kindle. Erfahren Sie mehr
  • Statt: EUR 29,63
  • Sie sparen: EUR 0,29 (1%)
  • Alle Preisangaben inkl. MwSt.
Nur noch 5 auf Lager (mehr ist unterwegs).
Verkauf und Versand durch Amazon.
Geschenkverpackung verfügbar.
Menge:1
Big Data For Dummies ist in Ihrem Einkaufwagen hinzugefügt worden
+ EUR 3,00 Versandkosten
Gebraucht: Gut | Details
Verkauft von BookOutlet Germany
Zustand: Gebraucht: Gut
Kommentar: Scratch & dent version. Book may have some cosmetic damage (i.e. dented corner..). Ships from Canada by Air Mail - Delivery within 10 business days - Customer Service available only in English
Ihren Artikel jetzt
eintauschen und
EUR 3,57 Gutschein erhalten.
Möchten Sie verkaufen?
Zur Rückseite klappen Zur Vorderseite klappen
Anhören Wird wiedergegeben... Angehalten   Sie hören eine Probe der Audible-Audioausgabe.
Weitere Informationen
Alle 4 Bilder anzeigen

Big Data For Dummies (Englisch) Taschenbuch – 19. April 2013

1 Kundenrezension

Alle 2 Formate und Ausgaben anzeigen Andere Formate und Ausgaben ausblenden
Amazon-Preis Neu ab Gebraucht ab
Kindle Edition
"Bitte wiederholen"
Taschenbuch
"Bitte wiederholen"
EUR 29,34
EUR 10,94 EUR 9,66
16 neu ab EUR 10,94 5 gebraucht ab EUR 9,66

Hinweise und Aktionen

  • Große Hörbuch-Sommeraktion: Entdecken Sie unsere bunte Auswahl an reduzierten Hörbüchern für den Sommer. Hier klicken.


Wird oft zusammen gekauft

Big Data For Dummies + Predictive Analytics For Dummies + Data Mining For Dummies
Preis für alle drei: EUR 93,14

Die ausgewählten Artikel zusammen kaufen
Jeder kann Kindle Bücher lesen — selbst ohne ein Kindle-Gerät — mit der KOSTENFREIEN Kindle App für Smartphones, Tablets und Computer.



Produktinformation

  • Taschenbuch: 336 Seiten
  • Verlag: John Wiley & Sons; Auflage: 1. Auflage (19. April 2013)
  • Sprache: Englisch
  • ISBN-10: 1118504224
  • ISBN-13: 978-1118504222
  • Größe und/oder Gewicht: 18,8 x 1,7 x 23,6 cm
  • Durchschnittliche Kundenbewertung: 4.0 von 5 Sternen  Alle Rezensionen anzeigen (1 Kundenrezension)
  • Amazon Bestseller-Rang: Nr. 25.244 in Fremdsprachige Bücher (Siehe Top 100 in Fremdsprachige Bücher)
  • Komplettes Inhaltsverzeichnis ansehen

Mehr über die Autoren

Entdecken Sie Bücher, lesen Sie über Autoren und mehr

Produktbeschreibungen

Buchrückseite

Learn to:
* Leverage big data tools and architectures
* Explore how big data can transform your business
* Integrate structured and unstructured data into your big data environment
* Use predictive analytics to make better decisions
 
Here's the guide that can keep big data from becoming a big headache!
 
Big data can be a complex concept. For Dummies to the rescue! Here's a plain-English explanation of what big data is (and isn't), the technology and database options supporting it, analytics that help you get meaning from your data, how to manage it, and what it can do for your company. Business executive or IT person, here's what you need to know.
* What it is - get your mind around big data from both a technical and business perspective
* Organize it - meet the big data stack and learn about different architectural levels, operational databases, organizing databases, and analytical data warehouses
* Big data computing model - explore distributed computing as well as the power of virtualization and the cloud
* Hadoop and MapReduce - learn the importance of Hadoop and MapReduce for big data analysis
* Get analytical - identify analytics tools for big data and evaluate the various new models that are evolving
* Ready? Implement - discover how to implement your big data solution with an eye to operationalizing and protecting your data
* What it means - see the importance of big data to your organization and how it's used to solve problems
 
Open the book and find:
* A definition of big data
* Profiles of various available technologies
* The role of the cloud
* How MapReduce aids big data management
* Why Hadoop is so important
* Some specific uses for text analytics
* How to approach big data security and privacy
* Ten best practices for managing big data

Über den Autor und weitere Mitwirkende

Judith Hurwitz is an expert in cloud computing, information management, and business strategy. Alan Nugent has extensive experience in cloud-based big data solutions. Dr. Fern Halper specializes in big data and analytics. Marcia Kaufman specializes in cloud infrastructure, information management, and analytics.

Welche anderen Artikel kaufen Kunden, nachdem sie diesen Artikel angesehen haben?


In diesem Buch

(Mehr dazu)
Ausgewählte Seiten ansehen
Buchdeckel | Copyright | Inhaltsverzeichnis | Auszug | Stichwortverzeichnis | Rückseite
Hier reinlesen und suchen:

Kundenrezensionen

4.0 von 5 Sternen
5 Sterne
0
4 Sterne
1
3 Sterne
0
2 Sterne
0
1 Sterne
0
Siehe die Kundenrezension
Sagen Sie Ihre Meinung zu diesem Artikel

Die hilfreichsten Kundenrezensionen

Format: Kindle Edition Verifizierter Kauf
This Dummy Book explains what big data is all about, how to use in (in theory) and what kind of tools are available. It explains a lot in general. I missed case studies and real world examples a bit.
Kommentar War diese Rezension für Sie hilfreich? Ja Nein Feedback senden...
Vielen Dank für Ihr Feedback. Wenn diese Rezension unangemessen ist, informieren Sie uns bitte darüber.
Wir konnten Ihre Stimmabgabe leider nicht speichern. Bitte erneut versuchen

Die hilfreichsten Kundenrezensionen auf Amazon.com (beta)

Amazon.com: 33 Rezensionen
34 von 40 Kunden fanden die folgende Rezension hilfreich
Big words for dummies 26. August 2013
Von Vasan Subramanian - Veröffentlicht auf Amazon.com
Format: Taschenbuch
I regret buying this book. No, it's not the money that I paid, I regret the time I spent trying to see if there was something that I could learn in it.

The book is a LOT of verbiage and adjectives. "Massive" or "scalable" finds its place in almost every page. In one page, I found 5 instances of "massive". Here is another extreme example: "Sparse, distributed, persistent multidimensional sorted map." There are at least three occurrences of that exact phrase.

If you want echo the hype that Big Data is great and learn all the jargon that is used in it, this book is for you. If you want to know why, or get down to fundamentals, skip it. There are typos (eg, [...] and factual inaccuracies (eg, the definition of unstructured data.) There are also completely incomprehensible examples under the garb of "code".

The book says little more than "Big Data is lot of data, you got to deal with it bit by bit". And it takes quite a few words to say that. It has no depth. Even when reading the last chapter, you feel that you're reading the introduction.
20 von 23 Kunden fanden die folgende Rezension hilfreich
Inexcusably bad writing 6. Dezember 2013
Von TJ - Veröffentlicht auf Amazon.com
Format: Taschenbuch
Incoherent. It was amazing to read things I understood already, and not understand the explanations. Apparently written piecemeal by committee.
34 von 42 Kunden fanden die folgende Rezension hilfreich
Glib, rambling and incoherent 6. September 2013
Von Dana Robinson - Veröffentlicht auf Amazon.com
Format: Taschenbuch
First, my background: I am a data and software architect at a company that produces software to handle very large quantities of scientific data. I picked this book up to see if it were worth recommending to other people at my company. (spoiler: it is not)

This book uses a lot of words to say very little and what it does say is often either incomplete to the point of uselessness or flat out wrong. The text is full of buzzwords and jargon, often used incorrectly. The figures are laughably useless (see figure 3-2 for a GREAT example). I think that the problem might be that Hurwitz and co. are business consultants and possibly in the habit of creating poorly researched, content-free, and buzzword-heavy prose for people with a limited depth of knowledge.

I would not recommend this book to anyone. Well, maybe I'd recommend it as a great example of very bad technical writing, but that's about it. I have no idea how other people are giving this five stars. Perhaps they are sockpuppet accounts.

Sadly, I don't know of a good introduction to the myriad of technologies that falls into the "big data" category. Such a book would be difficult to write well since it would have to make many complicated topics understandable to a novice.
2 von 2 Kunden fanden die folgende Rezension hilfreich
Helpful for the Uninitiated 12. April 2014
Von Edward J. Barton - Veröffentlicht auf Amazon.com
Format: Taschenbuch Verifizierter Kauf
My Engineering department constantly talks about Hadoop, Sqoop, Pig and Hive, and I was afraid that the zookeeper they referred to was somehow a real thing. So, I bought Big Data for Dummies. If you are brand new to the world of big data, the book will be a decent resource. You'll get the bulk of the buzzwords, a fair bit of general information, and some useful things to consider as part of the implementation process (where as a business leader, I needed to learn something) in the book. Sections of it are written for folks who may have a bit stronger engineering background than my one FORTRAN class 20 years ago, and these sections are pretty tough to comprehend.

I wish it had more general business elements, and the sections that deal with the problems and challenges of big data (Parts 5-7) are probably the most useful to the business generalist. If they could plus these up in the next edition, it would be great.

However, if you are looking for a quick read to get a general idea of what this is all about, it's an OK book - probably 3.5 stars, candidly...
2 von 2 Kunden fanden die folgende Rezension hilfreich
Good Introduction 11. Mai 2014
Von Amazon Customer - Veröffentlicht auf Amazon.com
Format: Taschenbuch
It covers a lot of aspects of big data, topics include:

• Why big data is different than the traditional data management: (3 V's). CRAP data instead of CRUD data.
• Why distributed computing/parallel computing is important for big data analysis.
• The big data stack, storage (physical), management (database, file system, etc), analysis (big data warehousing), and applications.
• Why virtualization (of server, network, storage etc) is important for Big data ecosystem, while not strictly required.
• Why public cloud (such as Amazon, Google, MS Azure) is important for Big data implementation, while not strictly required.
• Survey of big data management (databases) , from traditional RDBMS to non-relational DB, KV DB, Document DB, Column Oriented DB, etc, etc.
• Big data analysis, MapReduce, Hadoop, Traditional Data Warehousing.
• Big data implementation, operation, applications.

While not covering all the topics in great technical details and depth, it does give very good overviews.
Waren diese Rezensionen hilfreich? Wir wollen von Ihnen hören.