Big Data: The 5 Vs Everyone Must Know

Big Data is a big thing. It will change our world completely and is not a passing fad that will go away. To understand the phenomenon that is big data, it is often described using five Vs: Volume, Velocity, Variety, Veracity and Value

I thought it might be worth just reiterating what these five Vs are, in plain and simple language:

Volume refers to the vast amounts of data generated every second. Just think of all the emails, twitter messages, photos, video clips, sensor data etc. we produce and share every second. We are not talking Terabytes but Zettabytes or Brontobytes. On Facebook alone we send 10 billion messages per day, click the "like' button 4.5 billion times and upload 350 million new pictures each and every day. If we take all the data generated in the world between the beginning of time and 2008, the same amount of data will soon be generated every minute! This increasingly makes data sets too large to store and analyse using traditional database technology. With big data technology we can now store and use these data sets with the help of distributed systems, where parts of the data is stored in different locations and brought together by software.

Velocity refers to the speed at which new data is generated and the speed at which data moves around. Just think of social media messages going viral in seconds, the speed at which credit card transactions are checked for fraudulent activities, or the milliseconds it takes trading systems to analyse social media networks to pick up signals that trigger decisions to buy or sell shares. Big data technology allows us now to analyse the data while it is being generated, without ever putting it into databases.

Variety refers to the different types of data we can now use. In the past we focused on structured data that neatly fits into tables or relational databases, such as financial data (e.g. sales by product or region). In fact, 80% of the world’s data is now unstructured, and therefore can’t easily be put into tables (think of photos, video sequences or social media updates). With big data technology we can now harness differed types of data (structured and unstructured) including messages, social media conversations, photos, sensor data, video or voice recordings and bring them together with more traditional, structured data.

Veracity refers to the messiness or trustworthiness of the data. With many forms of big data, quality and accuracy are less controllable (just think of Twitter posts with hash tags, abbreviations, typos and colloquial speech as well as the reliability and accuracy of content) but big data and analytics technology now allows us to work with these type of data. The volumes often make up for the lack of quality or accuracy.

Value: Then there is another V to take into account when looking at Big Data: Value! It is all well and good having access to big data but unless we can turn it into value it is useless. So you can safely argue that 'value' is the most important V of Big Data. It is important that businesses make a business case for any attempt to collect and leverage big data. It is so easy to fall into the buzz trap and embark on big data initiatives without a clear understanding of costs and benefits.

I have put together this little presentation for you to use when talking about or discussing the 5 Vs of big data:

I hope this was useful? For more in-depth reading on big data, check out my The Big Data Guru column, or have a look at these recent posts I wrote for LinkedIn:

• 10 Awesome Ways Big Data Is Used Today To Change Our World
• Big Data: The Mega-Trend That Will Impact All Our Lives
• People Management: Data and Analytics Will Change It Forever
• Big Data: The Sexy and Creepy Side Of A Global Mega Trend
• Is Big Data the Single Biggest Thread To Your Job?

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About : Bernard Marr is a globally recognized expert in strategy, performance management, analytics, KPIs and big data. He helps companies and executive teams manage, measure, analyze and improve performance. His new book is: Big Data: Using Smart Big Data, Analytics and Metrics To Make Better Decisions and Improve Performance

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