Big Data is defined, by the Gartner Group, as information that includes the following four dimensions: velocity, variety, volume and veracity. Those four are what make Big Data unique or different than normal data.
Velocity refers to how long a company has to be able to process the information. The analysis needs usually needs to be completed in a short amount of time. Today's customer or order data needs to be analyzed before tomorrow.
Volume refers to the amount of data. Big Data works with terabytes and petabytes of data on market information, customer sentiment across social media channels, input from other enterprise systems (like shipping, credit card processing, etc.).
Variety refers to the fact that Big Data deals with tables in databases as well as unstructured data like video, audio, text, or other random sensor data. This isn’t just nice clean SQL tables. It’s messy data and metadata.
Veracity refers to the speed of the data flow. With Big Data, the signals, messages, and information come in too quickly to be processed by old technologies. As the number of sensors in the world increases, this becomes more important.
The term “Big Data” encompasses, not only these 4 dimensions, but also the new tech paradigms and algorithms for processing this data. MapReduce and Hadoop (built off MapReduce) are two important foundations of the Big Data revolution. MapReduce is a model that allows tasks to be performed across many computers, at the same time. Hadoop is a way of networking hardware together in a way that we can query across servers and databases faster.Below are some of the new Big Data courses we've recently released.