A couple of days ago I talked to a very good friend of mine, George Bonev of Software AG, about Big Data. George kindly explained to me the 3 Vs of BIG DATA (Volume, Velocity and Variety) which I like to share with you in this post. George actually spoke of 4 V’s, the fourth one being value for the customer. Although I do not disagree with his approach – from where I sit, creating value should be a given in whatever you are doing. If it does not create value it should not be done, should it? So I will focus on the 3V’s for the purposes of this post and I am sure he will be ok with this.
Volume – Volume describes the amount of data generated by organizations or individuals. BIG Data is usually associated with this characteristic. Enterprises of all industries will need to find ways to handle the ever-increasing data volume that’s being created every day. We certainly see this happen within our customer base – catalogues with over 10 million products in it have become more the rule then the exception. Some customers who not just manage products but also customers, and orders with hybris easily go beyond 1 TB of data.
Velocity – Velocity describes the frequency at which data is generated, captured and shared. Recent developments mean that not only consumers but also businesses generate more data in much shorter cycles. Because of the speed 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.
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. hybris’ rapid business objects (invented some 8 years ago) were a precursor of this trend; allowing enterprises to quickly introduce new data objects or extend existing objects with new characteristics.
- big data & the cloud will help to solve retail dilemmas
- Multi touch-points customer journeys – the 2nd riddle which BIG Data and the cloud may help to solve