Data Science vs Big Data

Data Science vs Big Data, What´s the difference?

Data Science vs Big Data, What´s the difference?

The terms Big Data and Data Science are associated with large volumes of data characterizing the new technological era. In particular, with the collection, analysis and, as an ultimate objective, extraction value of such data to aid in decision making. 

Both are closely related conceptually, but in no case are synonymous terms. In this post we will see the main differences between the two concepts from a conceptual approach that briefly define and place in their respective coordinates.

The concept relates to the efficient collection of a large volume of heterogeneous data (not stored in a traditional database) that can be structured, semi-structured or unstructured, to the storage and analysis in a short time, most sometimes in real time.

Although it is clear in general terms, it is a novel concept that encompasses a much broader scope of strictly technological -the term was introduced in the OxfordDictionary in 2013-, becoming a buzzword.

Besides being a buzzword, if it is still trend over time, it is because science data can get a great game. Not surprisingly, it has become an area of great interest for organizations of all kinds, sector and size. But what does it really mean?

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One of the main problems in finding a single definition is where we focus. On the one hand, they are often cited as distinctive three Vs: volume, velocity and variety, but as much as the size of the data counts, it is possible to identify as defining characteristics the tools used for analysis, or to focus all the attention in these.

In the absence of a universal definition, since there is no agreement on what is the “big data”, it has been proposed verydifferent definitions that, under the interest in everything related to Big Data, they have much less exhausted all the possibilities.

In general terms, we may agree that “Big Data” usually refers to large data, basically the scale of terabytes and petabytes (a petabyte is a million gigabytes), and its potential to deepen in our understanding of the phenomena that arouse our interest.

From the “physical and biological systems of human social and economic behaviour”, as theUC Berkeley Scool of Information notes on its website, to scientific objectives, business, concerning public administration or, of course, to any other susceptible area analysis.

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No doubt that the required analyzes to process the huge amount of data require technical resources and specific IT and algorithms that brings Data Science, a discipline that is in full swing, and it continues to grow under the umbrella of Big Data.

 



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