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3 Vs of Big Data explained !

With the huge amount and variety of data available, understanding big data analytics can be difficult. To understand better it is categorized into three segments commonly known as 3 Vs of Big Data. Volume, Velocity and Variety ( as discussed in the previous blog ).



Volume 
Data is being generated continuously from phones, cars, sensors, IoT Devices, healthcare equipment, videos, etc. Moreover, data is also being collected the way human behave, act and engage by the means of machine learning. Having more data means getting a better approach over competitors. 

This high volume of data requires equivalent storage and distributed approach to be accessible whenever required. However, many organisations fail to manage and decipher the collected data efficiently.
As the volume of data has increased, so have the options for storing data.
Data lakes, a central repository for all the data and analytics that allows organisations to store structured, unstructured and semistructured data at any scale has surpassed the Traditional approach of Data Warehouse storage method.

Velocity
As discussed in the previous blog with more data comes more opportunities. So, the speed at which the data is collected and analyzed is termed as Velocity. The speed at which data is generated must be collected, processed and stored at high speed. This collection and processing of data are known as Data processing.

According to, Digital universe by "IDC", Data around the world is increasing at an enormous speed out of which 3% of the data is organized, and only 0.5% is ready for analysis. Also, According to, "Social Skinny's knowledge", 293,000 statuses are posted, 136,000 photographs shared, and 500,000 comments posted on Facebook every minute.

Variety
Data is quick, data is immense, yet data is amazingly assorted. A couple of decades back, the data would've been in an ordered database in a straightforward book record. There was not a ton of alternatives on the most proficient method to utilize the data other than finding a pattern and basic characterization. 

Surely, big data has changed the data scene. While there's as yet a spot for content knowledge, there are different types of data presentation that are progressively advantageous. For example, video, sound, geospatial, pictures, and numerous others become an integral factor. 

Every data structure has its sort of uniqueness as far as how it's characterized and put away on a cloud. What makes the arrangement exceptional is how we can break down them to make important arrangements.

References : 

1. (Dumbill, 2012) Dumbill, E., 2012. Volume, Velocity, Variety: What You Need to Know About Big Data. URL https://www.forbes.com/sites/oreillymedia/2012/01/19/volume-velocity-variety-what-you-need-to-know-about-big-data/#322b1b311b6d (accessed 2.1.20).

2. Hansen, S., 2019. The 3 V’s of Big Data Analytics. The 3 V’s of Big Data Analytics. URL https://hackernoon.com/the-3-vs-of-big-data-analytics-1afd59692adb (accessed 2.1.20).


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