It is a no-brainer that big data consists of data that is large in volume. Normally, we can consider data as big data if it is at least a terabyte in size.


Big data can arrive at high velocities like real-time data and have to be processed in near real-time.


Since we collect as much data as possible, this means that big data can be varied. It can be structured or unstructured data. Additionally, it can be video, pictures, audio, and sensor data. Big Data solutions need to be able to handle this variety.


Lastly, big data has to be of some value to your organization. In order to be of value we have to make sure that it is correct.

Big Data Engineering

Big Data is data that is too large or comes in at too high of a velocity to deal with using normal data systems like Relational Database Management Systems or RDBMs. You more than likely have heard of the three V's of Big Data which are increasingly are referred to as the four V's of Big Data

Retail Industry

Companies have always collected retail data like transaction history but now that we have big data we can pull in other types of data to help us make better-informed business decisions which increases profit. In addition, with big data, we can get better insights into our customers buying habits via loyalty program data. We can use deep learning to analyze our customer behavior and predict when the best time to promote a product or service is for a set of customers with similar buying habits.

Medical Industry

Health care industry could use big data to prevent mediation errors, identifying high-risk patients, reduce hospital costs and wait times, prevent fraud, and enhance patient engagement. In addition, artificial intelligence is being used to help analyze radiology data like MRIs and XRays, which could reduce the number of exploratory surguries.

Transportation Industry

Big data can be found in the transportation industry to help with asset management, road infrastructure management, traffic management, and supply chain management. Big data helps to solve some of the worst traffic problems by using machine learning to better identify ways to mitigate traffic management issues. Using deep learning, artificial intelligence-based applications can make use of surveillance data to identify traffic problems and suggest solutions to those problems.

IT Industry

In IT, big data is being used to mitigate spam by using artificial intelligence to better identify the probability that a particular email might be spam. Deep learning algorithms help identify spam by being trained to identify historically identified pieces of spam email. In addition, big data and machine learning are used to better analyze system and applications logs to identify issues proactively and alert administrators more effectively.