Big Data Distilled

According to IDC, Big data technology and cloud demand will push global IT spending beyond $2 trillions in 2014. Spending on big data technologies should see a 30% rise, with $14 billions expected to be shelled out on the analysis of huge pools of data such as customer behavior and business performance. The following are supplemental Vs to better distill Big Data:

• Verification: Big Data solutions must comply with the regulations in the individual verticals, such as HIPPA for healthcare. Companies should have audits and verifiable evidence in adherence to regulatory requirements. Organizations also need to conform to standards and coding practices, which will promote interoperability and avoid lock-ins.
• Volatility: The volatility is about the valid duration of data and how long data need to be stored. In the case of real-time processing, time-sensitive data becomes irrelevant to the current analysis after a predefined period of time. On the other hand, certain data may have to be distributed or replicated to different sinks to process with distinct duration and persistence policies associated. 
• Vibrancy: Big Data has crossed the chasm to mature into the mainstream. Early adopters have got rewards in the payback to stay a step ahead of their competitors. Innovations continues with new services and products rolled out frequently. Rapid changes are a double-edged sword in this evolving space – opportunities to transform and revamp, but difficulties to catch up and keep pace with. Inexperience is also a big barrier and potentially costly bottleneck to a smooth implementation. 

For more information, please contact Tony Shan (blog@tonyshan.com) or leave your comments below. 

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