The 3 Vs of Big Data
Big Data Analytics
Businesses be it big or small have a huge responsibility of managing the
data they're collecting. In some cases, this can be done using excel sheets and
similar tools but in the case of companies with humongous amounts of data, the
traditional data processing techniques are not very useful and this is where
Big Data Analytics come into the picture.
The 3 Vs of Big Data

To make
sense of the above statement, experts have broken down the concept of Big Data
into three segments. They are:
- Velocity: Velocity refers to rate at which data is coming in and this is perhaps the most important aspect of the three and as Amazon's CEO Jeff Bezos rightly said, “speed matters in business”. With this he meant that companies who are good at making high velocity decisions will have an advantage in terms of speed and this can be done by processing the high volumes of data coming in at a high velocity using Big Data Analytics.
- Volume: The ‘Big’ in Big Data refers to the sheer volume of the data that defines Big Data. To put this in perspective, Facebook users alone upload 900 million photos on a daily basis. These users are more than the population of China and the ‘volume’ of this data is insanely large and needs Big Data analytics to process.
- Variety: The above example I gave in regards to Facebook photos being uploaded was just one type of data. There are other forms of data like posts, likes, comments and this data isn’t always structured. Thus, variety refers to data both structured and unstructured with 90% of it being unstructured thus requiring some pre processing before the data starts to make sense.
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