Top 3 myths of Big Data - HPC ASIA
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Top 3 myths of Big Data

Source: http://goo.gl/gClLVM

It is indeed hard for an organization today to exploit the full potential of Big Data. According to one study, “99.95% data is not even analyzed today”. Yet, despite how broadly Big Data is being discussed, it appears that it is still a very big mystery to many. In fact, outside of the experts who have a strong command of this topic, the misunderstandings around Big Data seem to have reached mythical proportions. Here are the top three myths.

 

Myth 1: Big data is only about substantial Data Volume:

Volume is just one main volume to define Big Data though it is the least important of overall three elements i.e. Variety and Velocity. The 3 V’s of Big Data according to the Gartner’s Doug Laney research report of 2001. Which implies that even if you get a real time stream of small data the challenge of managing and getting true insights will be similar to that of Big Data otherwise.

 

 

Myth 2:  Big Data Is Only At Fancy Term Right Now

According to the Gartner survey in 2014 interest in Big Data technologies and services is at a record high, with 73 percent of the organizations.

The stages of Big Data Adoption, 2013 and 2014 (Review Figure Below)

Note: The Gartner asked the survey respondents “Which of the 5 stages best describes your organization’s stage of Big data adoption”

Note: The Gartner asked the survey respondents “Which of the 5 stages best describes your organization’s stage of Big data adoption”

 

Myth 3: Big Data means Hadoop

Hadoop is an Apache open source software framework for working with Big data Big Data is too varied and complex for a one-size-fits-all solution. While Hadoop has surely captured the greatest name recognition, it is just one of three classes of technologies well suited to storing and managing Big Data.Hadoop is a great fit for staging vast amounts of raw data in order to extract summaries that can then be loaded into traditional enterprise data warehouses to conduct low-latency analytics. Real-time analytics, while making great advances on Hadoop with tools such as Presto and Apache Spark, are still best served by the traditional databases.

 

Do you have any myths that you want to share. Be a guest writer and write about your set of myths. Contact editor@hpc-asia.com today.

 

 

 

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