Data
The term Data comes from the Latin; its plural form “datum” means “to give”. Therefore, we can define data as “something given”.
In contemporary English, Datum (calendar date) and data (a piece of information) are separated lexemes.
In mediaeval times, the manuscripts were closed with the phrase “datum die (given on)”.
From mediaeval times to actual times, data has been changing its meaning. In the 18th century, significant inventions led the term data to change its purpose. Therefore, according to Rosenberg 2013, the term data corresponds to a factual representation, evidence from an experiment, experience and collection.
Data can be analyzed and studied to obtain relevant information that humans can interpret with appropriate tools. Thus, Data is a collection of given facts. Such data contain colossal variation. Consequently, we can define data as a sum of meanings through its entire origin and development.
Big
Big Data is an information explosion. What about the term Big? Big represents something significant. In other words, Big means something large in size. Therefore, Big allows us to capture the meaning of Big Data in a modern context.
Big Data is complex datasets coming from new sources. Such Data increase its Volume rapidly. These data sets are complex as traditional software tools cannot manage them. Thus, these voluminous data sets require new technology that can handle them.
A social network is an example of a complex system. Such a complex system generates Data rapidly. Such a dataset is considered then a Big Data.
What Big Data set is?
A large amount of data defines the Big Data term. Volume, Velocity, and Variety are the three Vs of Big Data. Consequently, handling terabytes of data to analyze faces challenges, Volume. Velocity is the rate at which the Data is being received. Lastly, Variety defines the type of Data that the Data sets obtained.
The three Vs of Big Data can be found easily in a Social Network.
Social Networks bring large amounts of unstructured data, Volume. Social Networks bring a plethora of data types; from clicks, sensors or any web app instance, we get Variety. Lastly, Social Networks have millions of users. Millions of users represent Volume and Velocity since every user creates Data at a rate never seen before.
Where Big Data is used?
The 4th industrial revolution is where Data lies. Data is considered the new gold. Problems such as storing significant amounts of data have been solved. Computational power has been increasing incrementally with time. Handling systems like Hadoop and Spark can manage data in big sizes; therefore, computational analysis has become an everyday task in companies.
Companies have been generating more data in the last two years than before. Studies suggest that data analysis covers only 1% of available data; therefore, where Big Data is used? Everyday. Thus, the data-driven economy is here — the foundations of cutting edge technologies produced entire rightful data sets.
Why does Big Data differ from Data Analytics?
Data Analytics brings data to the computer. Big Data Analytics brings computer power to Data.
Therefore Big Data is essential. Big Data is driving the new economy. Several new companies have emerged from Big Data Sets. The 4th industrial revolution started, and Big Data is the fuel.
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