The 3 Vs, explained.

The 3 Vs of Big Data

In my last post, I mentioned three Vs: variety, volume & velocity – big data’s defining characteristics.

Okay, cool…so…what did I actually mean by “defining characteristics”?

These traits set apart big data from ordinary datasets which can be processed by smaller, offline systems. Variety, volume and velocity require the assistance of ultra-powerful algorithms to assist humans in generating insights from the information gathered.

(Diya Soubra, 2012)

Variety: the combination of multiple data types in a given set. This includes both human-generated and machine-generated information, often intertwined. As described by Diya Soubra, from his 2012 blog post for Data Science Central, “The 3 Vs that define Big Data”, this data is found in multiple formats, structured and unstructured. (Soubra, 2012) Human-generated photos, audio, video and text are combined with machine-generated supplemental and metadata to assist with file storage and processing by other machines.

Volume: the large quantity of data generated by online transaction and interaction. To be considered “big” data, there must be massive amounts of information which cannot be analysed by humans alone. Data science shows that the volume of big data is increasing exponentially, estimated to reach 40 Zettabytes by the end of this year. This figure comes from Kasheeka Goel in his January 2020 piece, “What is Big Data?”, written for Intellipaat. (Goel, 2020)

Velocity: the speed of data generation and accumulation. Velocity dictates the rate at which big data is received from various sources. Data velocity varies by source and data type; certain sectors such as payroll and HR often receive big datasets in batches and process these at regular intervals, while web-based services like social media and media streaming receive real-time information about consumer interactions. Processing and understanding data must be done at a pace that matches the influx of information.  According to Brent Dykes of Forbes, velocity is a key requirement when it comes to generating insights – if a business can’t learn from their data sources and make quick strategic adjustments, data fails to become a valuable resource. (Dykes, 2017) Velocity depends on data type, platform and web speeds – however, there is an increasing need to process big data effectively, in real time, from sources like social media.

The three Vs that set apart big data from smaller data types also govern the processing of collecting and analysing virtual information. These standards will become increasingly important as the amount of online data continues to grow exponentially.

Sources:

Big Data: Forget Volume and Variety, Focus On Velocity [WWW Document], https://www.forbes.com/sites/brentdykes/2017/06/28/big-data-forget-volume-and-variety-focus-on-velocity/#1b874bb46f7d 

Clifford Lisette, n.d. What is Big Data? - Types, Advantages, and Characteristics - Intellipaat. Intellipaat Blog. URL https://intellipaat.com/blog/tutorial/hadoop-tutorial/big-data-overview/ 

The 3Vs that define Big Data - Data Science Central [WWW Document], n.d. URL https://www.datasciencecentral.com/forum/topics/the-3vs-that-define-big-data