Big data is increasingly being adopted by startups and small to large enterprises, owing to its ability to handle the huge volume, velocity, variety, veracity, and value of data. These five Vs, have become critical to define the regular big data that enterprises come across.
Enterprises today, based on their businesses receive a massive influx of data, in the range of hundreds of petabytes to tens of exabytes, from sources like social media feeds, webpage click & visit counts, follower count, demographic track, etc. This data all enclosed is massive in volume.
Next comes is the data velocity, owing to advancements in edge computing, its now possible to process the data near the source, instead of transmitting it to the cloud for processing. This source processing makes data processing in real-time a possibility, and thus maximum data velocity.
Follows is the data variety, which basically means the format of data. Owing to different sources of data, enterprises receive this data in many formats, which includes textual data, numeric data, audio & video clips, financial records, stock ticker data etc. Most of this data is either un-organized or not in the required format, for enterprise software to interpret, especially when it comes to audio & video clips, all this data needs to be processed first to generate enterprise relevant metadata.
Next in line is the data veracity, which in short points to data disturbance or inconsistency. On certain occasions, ceremonies, and events, data influx is so huge, that data management becomes extremely difficult.
Finally, the business value that the received data has, is of much importance. Today, with much-advanced data collection tools, having a massive reach, it is possible to cover the entire data space, fetching every possible data out there. But only relevant data can help businesses with actionable insights.