How big is big data?

A quote from Lewis Carrol, “If you don’t know where you’re going, any road will get you there.” that clearly shows the importance of marketing for any manufacturing unit. Whiteout a clear roadmap, which is accomplished by industrial marketing strategies, manufacturing units are working in a vague way. Analysis of Designated Marketing Area (DMA) is a way to manage ambiguity. The very first question that comes up is how to get the data, and then, how to analysis of this data.

Actually there is no single way of getting data for marketing purposes and creating DMA map. Nowadays credit cards companies are selling their customers data to businesses including their customers spending money habits and direction. How big it would be to collect all customers’ data? More than that, you can buy data from postal services or even from companies with search engine. Recently Google Home and Amazon Echo are capable of collecting data from their customers. If you gather all these data together, how big it would be?

Although big data is really big, still the volume does not completely define the nature of big data. In our marketing example, data has different format when you are collecting your data from different resources. It can be voice; data that was collected from google Home that should be converted to text, numbers; money data that was collected from credit card agencies, or even text; data that was collected from amazon review. So Variety of data is another factor of big data, which shows the different forms of data.

Another factor that defines the big data is the Velocity of data. Needless to say, getting data from any of those mentioned resources is an ongoing process, it is also known as streaming feature of data.  The last factor that defines the big data, it is the Veracity of data. There is always some degree of uncertainty toward the accuracy of data, especially when it comes to big data.

Volume, Variety, Velocity, and Veracity are four V’s of big data. IBM Big Data and Analytics Hub depicts these four factors in the below picture. For more information and getting to know about ongoing projects, please check my LinkedIn.

4-Vs-of-big-data.jpg

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Author: Amin Sabzehzar

MBA student Mechanical Engineer University of Nevada, Reno

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