3 V's OF BIG DATA

Big data is the extension of unstructured, semi-structured, and organized data generated from devices connected to the internet. The aim is to turn data into information and information into insights.(Hackernoon.com, 2019)

The perspectives obtained from big data analytics tools can allow advertisers to more efficiently target campaigns, help healthcare professionals identify epidemics, and help scientists consider future sustainability.

3Vs (volume, variety and velocity) are three defining characteristics or measurements of big data.

1) Volume refers to the data quantity.

2) Variety refers to the number of data types.

3) Velocity refers to the data processing speed.

VOLUME

There's a lot of data behind the universe, probably in an infinite number. With over 90 percent of today's data generated in the past 2 years. It is projected that 2.5 quintillion bytes of data are being produced annually, resulting in 40 zettabytes of data being created by 2020, reflecting a 300-fold rise from 2005. As a consequence, having Terabytes and even Petabytes of data in storage devices and on servers is not unusual for large companies today. (Big Data LDN, 2018)

Let's talk about the volume from a social media viewpoint because social media has an enormous impact on the numbers. There are more than 2 trillion posts posted since 2016 and 250 billion pictures uploaded. Facebook has huge amount of personal data, and every second of the data is accessed by its 2,2 billion people. That would not be feasible if it weren't for significant data growth. (Hackernoon.com, 2019)

We are obtaining a lot of data time and again. Every day Google alone returns to the internet, storing another 20 petabytes.  20 petabytes are 20,000 terabytes, 20 million gigabytes, 20 quadrillion bytes.  (The Great Courses Daily, 2017) (Hackernoon.com, 2019)

VELOCITY

The growth of big data would potentially lead to more incentives. There are plenty of data at hand, and once we have access to this data, you can use it to find new facts. Data growth rates surpass our ability to decode them. A study was carried out by IDC at Digital Universe indicates that data around the planet doubles in size every two years. More importantly, it organizes 3 % of the tests, with only 0.5 % available for analysis. Big data is not just large and vast; it is fast growing. The regular Facebook numbers for starters. Based on the experience of Social Skinny, it updates 293,000 statuses, uploads 136,000 photographs and posts 500,000 comments on Facebook per minute. Metadata infrastructure and Big Data analytics, together with machine learning and AI, must be used to their maximum potential to provide a snapshot of possible frontiers. (Hackernoon.com, 2019)

Google receives over 2 million search queries. And 200 million email messages are sent. (The Great Courses Daily, 2017)

VARIETY

Data is accessible, data is plentiful, but the data is very diverse. A few decades ago, data in a simple text file would have been in a structured database. Apart from seeing a pattern and a primary classification, there were not many choices on how to use the data. Big data obviously has changed the landscape of the world. While there's still a space for text data, there are other more accessible ways of data presentation. Image, audio, geospatial, pictures, and many others, for example, are entering play. What types of data has its own level of complexity about how it is handled and processed on a server? What is fascinating about the approach is how we can analyze them and create practical solutions. (Hackernoon.com, 2019)

For example, In the 1980s, the cost of a gigabyte was over a million dollars. So a 16-gigabyte-memory mobile would be a $16 million device. (The Great Courses Daily, 2017)

Therefore, with a lot of variety, we stand in a data deluge that rains vast volumes of data at high velocities. Information comes with all of this data as well as the opportunity for innovation comes with that data. Big data analytics tools can make it easier for companies to present information, make predictions and develop innovative solutions. Make sure that the data is accurate when using it so that it works properly. Big data analytics is, therefore, a necessary skill, which will become more challenging in the future.

BIBLIOGRAPHY:

Hackernoon.com. (2019). The 3 V's of Big Data Analytics. [online] Available at: https://hackernoon.com/the-3-vs-of-big-data-analytics-1afd59692adb [Accessed 9 Feb. 2020].

‌Big Data LDN. (2018). Big Data: The 3 Vs explained | BIG DATA LDN. [online] Available at: https://bigdataldn.com/intelligence/big-data-the-3-vs-explained/ [Accessed 9 Feb. 2020].

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The Great Courses Daily. (2017). Understanding Big Data: The Three V's. [online] Available at: https://www.thegreatcoursesdaily.com/understanding-big-data-three-v/ [Accessed 9 Feb. 2020].

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