3 Major Concerns with Strategic Big Data
Data Silos
A data silo is a separate database where a company can store it's infrequently accessed data. The problem with data silos is that this data is sometimes valuable and cannot be analyzed with new in-coming data once it is in a silo. A data silo segregates the infrequently accessed data into a compact area to get it 'out of the way.' Companies need to be careful of the amount of data that they send to silos; comparing past events with current events can yield many new discoveries and create value from the data.
Lack of Data Scientists
As we have already stated before, the amount of data is continuously increasing. This means we actually need an increasing amount of data scientists to construct new formulas for big data. We cannot allow the great advancements that strategic big data has to offer become stifled by a lack of available data scientists.
Lack of Communication
The last and most important link that needs to be addressed is a lack of communication. There is a need for improved communication between top executives and data scientists. The top executives need to be clear when asking what kind of data they want the scientists to analyze and the scientists need to make suggestions about data they think may be important to analyze. It takes both sides to open up communication.
Work Cited: Singh, Gurjeet. December 4, 2013. The 3 Big Problems in Big Data (hint: they all involve people). Venture Beat News. Retrieved from http://venturebeat.com/2013/12/04/the-3-big-problems-in-big-data-hint-theyre-all-about-people/
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