The 6th V of Big Data
Note: This post was adapted from a version originally written for versor.com.au
People love memory aids, especially when it comes to learning lists of technical jargon. So it is not surprising that when Doug Laney wrote his paper “3D Data Management: Controlling Data Volume, Velocity and Variety” in 2001, that these soon became the 3 V’s of Big Data.
Volume refers to the large amounts and scale of data that is being generated and stored. This is especially true as IOT devices, often prodigious producers of data, are increasingly embedded virtually everywhere. Velocity refers to the speed at which data is generated and expected to be consumed. Whole areas of technology had to be invented just to facilitate consumption of streaming data at speed. Variety refers to the range of types of data that can be generated. This includes – amongst others, structured, unstructured, image, and audio data. Within each of these types, there are also multiple formats to be found, which may require specialised knowledge or software to access.
Soon after these, two more V’s were added – Veracity and Value. Veracity, one of the most important aspects of data handling, refers to understanding the provenance of data, its quality, integrity and how complete it is, and therefore how much it can be trusted to answer particular questions.
Value, the final V, is whether the data contains worth. Just because data is available, is it worth anything? Can you use it for a social, health or commercial benefit?
These 5 aspects of Big Data are important, and together go most of the way to define it. However, I believe that a 6th important aspect of Big Data rounds out the ‘V’s – Vision.
Why Vision? Because without vision you can collect all the data in the world, and it can sit in your data lake or data warehouse, but all it will do is gather dust – and likely cost you storage fees.
Vision is the ability of an enterprise to transform data into insight, to plumb its depths and wring it out until it yields the means to be able to transform lives, businesses and processes. This is not just hyperbole, it is actually the responsible attitude to take when formulating a data strategy.
Your Analytics and AI Strategy formulation process should always include workshops to pinpoint a business’ vision – which should be targeted with appropriate AI and analytics, so you can meet the future head-on!
