Big Data can be defined as extremely large data sets that may be analyzed computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions.
Big data can be described in terms of data management challenges that – due to increasing volume, velocity and variety of data – cannot be solved with traditional databases. While there are plenty of definitions for big data, most of them include the concept of what’s commonly known as “three V’s” of big data:
Volume: Ranges from terabytes to petabytes of data
Variety: Includes data from a wide range of sources and formats (e.g. web logs, social media interactions, ecommerce and online transactions, financial transactions, etc)
Velocity: Increasingly, businesses have stringent requirements from the time data is generated, to the time actionable insights are delivered to the users. Therefore, data needs to be collected, stored, processed, and analyzed within relatively short windows – ranging from daily to real-time