Ebook Planning for Big Data, by Edd Dumbill
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Planning for Big Data, by Edd Dumbill
Ebook Planning for Big Data, by Edd Dumbill
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In an age where everything is measurable, understanding big data is an essential. From creating new data-driven products through to increasing operational efficiency, big data has the potential to make your organization both more competitive and more innovative.
As this emerging field transitions from the bleeding edge to enterprise infrastructure, it's vital to understand not only the technologies involved, but the organizational and cultural demands of being data-driven.
Written by O'Reilly Radar's experts on big data, this anthology describes:
- The broad industry changes heralded by the big data era
- What big data is, what it means to your business, and how to start solving data problems
- The software that makes up the Hadoop big data stack, and the major enterprise vendors' Hadoop solutions
- The landscape of NoSQL databases and their relative merits
- How visualization plays an important part in data work
- Published on: 2012-03-12
- Released on: 2012-03-12
- Format: Kindle eBook
Most helpful customer reviews
2 of 2 people found the following review helpful.
High level introduction to addressing Big Data in the enterprise
By Erik Gfesser
While at first glance potential readers might see this white paper sized text as overlapping with another recent O'Reilly Radar Team publication, "Big Data Now: Current Perspectives from O'Reilly Radar", this work is really intended to focus on what Big Data is all about, why it matters, and where to get started, whereas the earlier text covered a much broader spectrum of Big Data related material. In addition, while management is part of the target audience for both, the earlier text is also more technical in the sense that it gets down to programmatic levels in a few places, and also discusses technology stacks that this book does not cover.
After a discussion of how a company collects, analyzes, and acts on data, and a walk through different aspects of Big Data, the editors shift the discussion to a very high level overview of the Apache Hadoop ecosystem, followed by a Big Data market survey somewhat akin to what one might find from Gartner that focuses on enterprise software vendor distributions of Hadoop, Big Data cloud platforms, and data markets, and brief entries on the NoSQL movement, data visualization, and O'Reilly Radar Team expections from the Big Data landscape over the coming year.
Readers are gently led through the current Big Data landscape. For example, as the author of the second chapter states, "Big data is data that exceeds the processing capacity of conventional database systems. The data is too big, moves too fast, or doesn't fit the structures of your database architectures. To gain value from this data, you must choose an alternative way to process it. The hot IT buzzword of 2012, big data has become viable as cost-effective approaches have emerged to tame the volume, velocity, and variability of massive data. Within this data lie valuable patterns and information, previously hidden because of the amount of work required to extract them."
Although this book contains different material than "Big Data Now: Current Perspectives from O'Reilly Radar", as a consultant I think technical audiences new to this space will prefer this earlier work. In addition, it is rather apparent that "Planning for Big Data: A CIO's Handbook to the Changing Data Landscape" emphasizes commericalized open source products, and does not cover tooling outside of the Hadoop ecosystem to any great extent. While this book is 25% shorter, and is understandably targeted at senior management, many potential readers will likely appreciate the more extensive coverage of this space in the earlier text.
1 of 1 people found the following review helpful.
Excellent introduction to big data and the logistics of data science
By Gale Stafford
I do a lot of work in IT operations, business analysis, and HR consulting. The past year or so, I've seen a rapid increase in data science jobs and general excitement around big data. A couple weeks ago, the American Psychological Association ran a story about firms hiring business psychologists to join data science teams. So this seems to be a hot area and the "hype" represents not a temporary blip but a genuine trend that will continue to strengthen.
What I like about this book is the ease of reading it. I have not done any work with big data but I understood everything I read. The book covers all the major companies offering services for data scientists and administrators of systems that process big data. I feel current with my knowledge since the book was written in 2011-2012 from what I can tell.
Overall, I'd say the impressive thing about this book is the quality writing and the authors' collective ability to engage a reader who is not working in big data yet, but wants to.
0 of 0 people found the following review helpful.
A decent high-level view into the world of big data.
By Amazon Customer
Planning for big data gives a 50000 foot view into the world of big data and data science. It is perfect for the big data newbie and the author even says if you're already working with big data you should give the book to a friend. I found it be a easy read that didn't take longer than 3 or 4 hours.
The author glosses over the main areas of big data and provides almost a list of relevant technologies and services. After reading this book you can get a small glimpse of how large the big data world is.
Then author begins with why organizations are interested in big data and analyzing their data as quickly as possible. Then we're introduced to some of the technologies that make it possible, such as Hadoop.
Cloud computing is a big player in big data and the author gives great comparisons of the main cloud providers, specifically amazon Google and Microsoft. It was very useful to have a side by side comparison of the services and the features they offer.
The author also lists out many of the nosql solutions available and why a nosql solution can be beneficial for big data. He emphasizes an agile approach and how nosql allows developers to easily build on existing structure and how it helps to scale horizontally.
And the last main piece that is mentioned is the importance of visualizations that are interactive and that can communicate complex ideas, as the author puts it, these are different than the normal boring bar graphs and charts put into slide presentations.
In summary I felt Planning for Big Data was a great starting point for someone who's beginning to explore the world of big data and it might even be useful for someone who is a little more familiar with big data to use as a reference of other tools and services that are available.
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