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101 "Insanely Great" Resources -- Big Data [Kindle Edition]

Benjamin Kerschberg
5.0 out of 5 stars  See all reviews (2 customer reviews)

Kindle Price: $2.99

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Book Description

101 "Insanely Great" Resources -- BIG DATA is an easy-to-use introduction to the world of Big Data, and in particular to 101 important resources for understanding the topic. This e-Book / PDF is filled with embedded links that take you directly to the Big Data section of a particular resources (e.g., The Wall Street Journal) or to more specific sites such as Data Science Central or journals.
Why is this resource important?
Big data is a combination of old and new technologies that helps companies gain actionable insight.
Rather than think of big data as a particular data set, one can derive a higher value proposition by managing a huge volume of disparate data at the right speed and within the right frame of time to allow
real-time analysis reaction and behavior modification. Big data is typically broken down by four characteristics:
• Volume: How much data;
• Velocity: How quickly that data is processed;
• Variety: The various types of data; and
• Veracity: How accurate is the data? This is the most important of the four categories.
While these four “V”s are a helpful framework, they can be misleading and overly simplistic. For example, a company may have huge volumes of very simple data; by contrast, another may have a smaller amount of much more complex unstructured data. Even more important is the data’s veracity. How accurate is that data in predicting business value?
Data must be able to be verified based on both accuracy and context. It is also important to identify the right amount of data that can be analyzed to impact business outcomes.
Implementing big data processes is not easy. According to Gartner:
Companies deploying big data projects to production were initially, and correctly, focused on deriving business value and developing their big data strategy. As enterprises realize value from these projects, and they become more entrenched in the business, big data efforts will have to mature. Enterprises must evolve infrastructure and skills to maximize big data investment [so that] new data sources make big data valuable.
In this respect, it is important to remember that actionable knowledge is not inherent to data per se; rather, it must be extracted based on rules and algorithms.
All of this begins with Big Data, and these 101 resources will get you well underway.

About the Author

Ben Kerschberg is a contributor to Forbes, Harvard Business Review, The Wall Street Journal, and The Huffington Post. He is a GigaOm Pro analyst and was named by Analytics Weekly (2014) as a top contributor in the fields of Big Data and Analytics. He is the author of three books. He graduated from Yale Law School and the University of Virginia.

Product Details

  • File Size: 2111 KB
  • Print Length: 31 pages
  • Publisher: BK Literary Enterprises LLC (April 2, 2014)
  • Sold by: Amazon Digital Services, Inc.
  • Language: English
  • Text-to-Speech: Enabled
  • X-Ray:
  • Lending: Enabled
  • Amazon Best Sellers Rank: #637,562 Paid in Kindle Store (See Top 100 Paid in Kindle Store)
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Most Helpful Customer Reviews
2 of 2 people found the following review helpful
5.0 out of 5 stars A Must-Have For The Tech Junkie April 4, 2014
Format:Kindle Edition|Verified Purchase
The author separates the wheat from the chaff so you can find truly valuable Big Data resources. As a busy entrepreneur I am grateful that Mr. Kerschberg has saved me countless hours, (which truth be told the end result still wouldn't be as meticulous and valuable as what has been provided).
If Big Data matters to you, then this book is a godsend.
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1 of 1 people found the following review helpful
5.0 out of 5 stars Finally, a great curated resource on Big Data April 4, 2014
Format:Kindle Edition|Verified Purchase
I liked @benkerschberg to-the-point lists of top influencers in #DataMining

This will help those getting started in the field, as well as those looking for additional resources.

Larry Kerschberg
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