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The Promises and Limitations of Big Data

Amaya Martin

Through the continuous collection and analysis of big data, organizations can increase revenue, yet with so much buzz surrounding big data analysis, it is only fair to discuss what the promises and limitations of big data analysis are.

Big Data Promises

Improved Data Management

With data processing services, analysts will be able to gather and analyze data with efficiency and ease. All it takes to use such a platform is a basic technical know-how to define the storage and analysis of data.

The abstraction property lets users work with data simply without any complicated steps, which enables data of different formats to be scanned specifically for particular purposes.

Speed, Capacity and Cloud Support

Cloud Hosting services can be used for storing and analyzing large amounts of data, for they provide the computing power necessary to process data for a specific period of time. This relieves organizations from making significant capital investments for hardware while allowing them to analyze massive data sets with higher computational ability.

Users Can Visualize Data

With huge amounts of data being processed, visualization tools are required to present data in an easy-to-read format. The big data service provides such a format. Leading service providers have shifted the focus of the service from being IT-driven, to being an analytics model. This results in better returns and accelerates adoption.

The Limitations of Big Data

Like any other tool, big data suffers from the following limitations:

Data Doesn’t Guarantee

For example: A recent hiring policy found that there was no correlation between a candidate’s academic achievement and work performance. This study proved that big data can be misleading. The bottom line: Big data does not guarantee characteristics.

Lost In Translation

Multiple layers of data can appear to be different, but there is no way to know. Data translation causes confusion and increases the complexity of data handling. As a result, analysts have to screen multiple data sets within a single entity.

About the author: Amaya Martin, working as a Content writer at MyRealtimeCloud is a proficient writer of the technology sector. Topics like upcoming PC and mobile application software; tax software, etc., has always grabbed her interests. Her previous articles on Hosted QuickBooks and other application softwares have been liked by many active readers of the technology sector.

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