Sample Solution

If we think about personal data storage, the average person has a phone that may have 64GB of data, or a computer hard drive ranging from 500GB to 4TB. As an individual, it might take an individual some years to fill out all that storage space. In 2012 about 2.5 exabytes (that’s a million terabytes) of data was generated every day and that doubles every 40 months. (Andrew McAfee, 2012) So the obvious question becomes, how do you store all this data? More hard drives, a dedicated server, cloud storage are all viable answers but they all costs a lot of money when talking about the sheer volume of data that is being collected every day. The challenge of management is more a question of how much data is needed to make meaningful decisions, how much data is worth holding onto and what storage systems should be used?

Velocity

This is really talking about the speed at which data is being formed. Having data being formed at real-time (or as close as can be managed) is useful for companies to respond to changes as fast as possible, thus giving them an advantage over the competitors. Imagine being a hotel and knowing how many people where travelling in your direction at any given time? Knowing if they had accommodation already sorted out or not, knowing what type of rooms they wanted and so on, as a hotel you could start to tailor an offer directed to a specific individual before they even get to you. Harvesting real time is in of itself a hassle, sometimes even unethical (eg. “Always on” technology listening to private conversations) and can require a great deal of infrastructure to set up.

Amazon has an algorithm that collects real time data on peoples shopping habits, what they are looking at, what they buy with other products and so on to create a predictive algorithm that will suggest things the customer is known to like or combine with other products, so that if somebody puts weight lifting gear into their basket it might suggest liquid chalk.