5 Reasons to Read “Big Data Analytics for Dummies”


Wikipedia describes “Big Data” as a broad term “for any collection of data sets so large and complex that it becomes difficult to process using on-hand data management tools or traditional data processing applications.” Forbes identified these “5 Things Managers Should Know About The Big Data Economy” which are great reasons to read IBM’s Dummies book:

1. We Now Create Knowledge Without Expertise
2. We Can Attain “Scale Without Mass”
3. Data Is The New Capital
4. Privacy Will Become A Brand Value
5. The Semantic Economy

“Big Data” analytics can be critical for competitive advantages and are considered by many businesses to be “one of the world’s most valuable resources” as explained in the IBM Limited Edition of “Big Data Analytics Infrastructure for Dummies” published in 2014 which includes a description of 3 V’s of Big Data and Analytics (BD&A):

Volume. The first attribute of Big Data is volume. Big Data projects tend to imply terabytes to petabytes of information. However, some smaller industries and organizations are likely to deal with mere gigabytes or terabytes of data.

Velocity. The second attribute of Big Data is velocity — the speed at which information arrives, is analyzed, and is delivered. The velocity of data moving through the systems of an organization varies from batch integration and loading of data at predetermined intervals to real-time streaming of data. The former can be seen in traditional data warehousing. The latter is in the world of technologies such as complex event processing (CEP), rules engines, text analytics, inferencing, and machine learning.

Variety. The third attribute of Big Data is variety. In the past, enterprises had only to deal with a manageable number of data sources. Times have changed. Today’s business environment includes not only more data but also more types of data than ever before. Disparate data is data from a variety of data sources and in a variety of formats, and is a major challenge that business business analytics and Big Data projects must contend with.

As Big Data expands it will impact every business, so everyone needs to understand Big Data.

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