The heart of Big Data definition
The phrase Big Data was popularized in the early 2000s and specifically talks about Volumes of data being received at Velocity by organizations in a Variety of different formats. These three V’s are at the heart of any Big Data definition.
Big Data talks about massive volumes of unstructured data. Companies collect data from a variety of different sources. These include sales transactions, IoT sensors, audit information, social media and more. While the amount varies by organization, it is safe to say that this amount of data is more than a single individual could process.
With millions of different IoT devices already connected and more coming online daily, companies are having to handle massive amounts of data that is coming in at speed. Velocity does not just speak to the speed at which data is being received, but also to the speed of systems that act on this data.
Variety covers the fact that data being received is not of one specific type. Traditionally, data could be accessed and stored in a simple database. That is no longer the case, as data now comprises many different types and includes video, text, audio and more.
More recently the definition of Big Data has expanded to include Value and Veracity. The two new V’s speak to the fact that while data by itself has intrinsic value, it is not really useful to the world until that value is realized. Similarly, with veracity, if data is incorrect, then it is unreliable and cannot be used.
Understanding Big Data in the Real World
Data is not just being generated by humans anymore. With more and more devices being connected to the Internet daily, data is being generated at an ever-increasing rate. Big data helps to take this information and transform it into something actionable.
Big Data can help companies to make smart decisions faster and more efficiently. Data coming from a multitude of different sources can be analyzed with a host of different tools to provide meaningful insights for company leaders.
How Big Data Works in the World of AI
When Big Data is paired up with AI, efficiencies can be dramatically improved. AI with its ability to learn can search for specific patterns and extrapolate out, based on the information obtained. With the help of AI, data analytics is less labor intensive as AI continues to create new systems and processes. While AI has not completely removed the need or requirement for people in the analysis phase, it has made it a less time intensive need.
One significant way that AI can help is through its ability to weed out outliers. This allows AI systems the intelligence to eradicate bad and duplicate data ensuring only useful information gets processed and used. By using information that is validated and correct, AI systems and tools are better able to predict future outcomes helping companies improve their overall strategy.