Data Is Exploding: The 3V’s Of Big Data

Data is exploding. In its 2010 BIG Data frontier report, McKinsey predicted a 60% increase in retailer operating margins with BIG Data, and this is why the technologies that enable it have become so important.

No organisation wants to pollute its transactional database with BIG data, but the demand for information is such that enterprises have to have data readily accessible so that analytics can run in real-time, giving enterprises a better chance to react to changing trends. It is helpful, therefore, to understand the 3 V’s of BIG Data – Volume, Velocity and Variety:

1. Volume

Volume describes the amount of data generated by organizations or individuals. BIG Data is usually associated with this characteristic. Enterprises across all industries will need to find ways to handle the ever-increasing data volume that’s being created every day. We certainly see this happening within our customer base – catalogues containing over 10 million products have become the rule rather than the exception. Some customers who not only manage products but also customers can easily go beyond 1 terra byte of data.

2. Velocity

Velocity describes the frequency at which data is generated, captured and shared. Recent developments mean that not only consumers but businesses generate more data in much shorter cycles. Because of the speed involved, enterprises can only capitalize on this data if the data is captured and shared in real-time. Today that’s where many analytics, CRM, personalization, POS or similar systems fall short. They can only deal with the data in batches every few hours, if at all, which renders the data worthless as the cycle of new data being generated has already begun.

3. Variety

A proliferation of data types from social, machine-to-machine and mobile sources add new data types to traditional transactional data. Data no longer fits into neat, easy to consume structures. New types include content, geo-spatial, hardware data points, location based, log data, machine data, metrics, mobile, physical data points, process, RFID’s, search, sentiment, streaming data, social, text and web. Our own rapid business objects (invented some 8 years ago) were a precursor to this trend; allowing enterprises to quickly introduce new data objects or extend existing objects with new characteristics.

Why is it important to understand this? Because BIG Data – or Data HD – helps to paint a better picture of customer interactions with an enterprise. It enables a better understanding of what customers would like to achieve at each touch-point, minimising the risk of losing them while migrating between touch-points and ensuring that relevant content is delivered to customers. So for enterprises to become more helpful, which customers love and to assist in converting them, it is important to remember the 3V’s of BIG Data.

In his over 10 years at hybris Stefan Schmidt has consulted for leading companies including Toys'R'Us, Virgin Megastores, Reebok, Waterstones/HMV, H&M and Rexel UK on their E-Commerce Strategy and Implementation. He has worked with many Retailers, Wholesalers, Manufacturers and Solution Providers from different markets during this time. In his current position he is responsible for the strategy of hybris' multichannel product stack, feeding back lessons learned in the field.