The more we hear about Big Data, the more confusing it gets. There are so many uses and so much information thrown at us, it’s hard to decipher what it all means. Here is a basic list of Big Data terminology that might help you next time you feel overwhelmed.
The original definition of big data were the three V’s. Volume, velocity and variety. Volume is the size of the data. Velocity is how quickly the data is acquired and used. The variety is the different types of data that can be collected and analyze. This is the most well-known definition. Eventually, they added several other V’s- validity, veracity value and visibility. Our post, Big Data Gets Defined…Finally, goes into further detail about the original definition.
Many businesses are using computer generated data, data from computers rather an a human. It can be clicks from and to websites, social media information from Facebook, Twitter and other popular sites, and it also can come from multimedia sites like YouTube.
Big Data Analytics: Software using algorithms and statistics to derive meaning from the data.
Database as a Service (DaaS): A database typically hosted in the cloud and works on a metered basis
Data Science: Incorporates statistics, data visualization, data mining and database engineering to solve problems
Data scientist: Those who work with data science
Data Visualization: Visual perception of data to derive meaning or communicate information effectively
MetaData: any data that describes other data
Semi-Structured Data: It is not structured by a formal data model but provides other ways of describing data
Software as a Service (SaaS): Software that is used over the web by a web browser
Structured Data: Data that is structured by a formal data model
Unstructured Data: This data has no identifiable structure
Contact Biel’s today with any inquiries about data or how it is used in your company.
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