101 ''Insanely Great'' Resources -- Big Data

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.