Big data is not a single technology but a combination of old and new technologies that helps companies gain actionable insight. Therefore, big data is the capability to manage a huge volume of disparate data, at the right speed, and within the right time frame to allow real-time analysis and reaction. Big data is typically broken down by three characteristics:
Volume: How much data
Velocity: How fast that data is processed
Variety: The various types of data
Although it’s convenient to simplify big data into the three Vs, it can be misleading and overly simplistic. For example, you may be managing a relatively small amount of very disparate, complex data or you may be processing a huge volume of very simple data.
That simple data may be all structured or all unstructured. Even more important is the fourth V: veracity. How accurate is that data in predicting business value? Do the results of a big data analysis actually make sense?
It is critical that you don’t underestimate the task at hand. Data must be able to be verified based on both accuracy and context. An innovative business may want to be able to analyze massive amounts of data in real time to quickly assess the value of that customer and the potential to provide additional offers to that customer.
It is necessary to identify the right amount and types of data that can be analyzed to impact business outcomes. Big data incorporates all data, including structured data and unstructured data from e-mail, social media, text streams, and more. This kind of data management requires that companies leverage both their structured and unstructured data.
