Augmented reality (AR)- the use of computer modeling and simulation that enables a person to interact with an artificial three-dimensional (3-D) visual or other sensory environment.  In a typical VR format, a user wearing a helmet with a stereoscopic screen views animated images of a simulated environment.

virtual reality (VR) - is an interactive experience of a real-world environment where the objects that reside in the real world are enhanced by computer-generated perceptual information, sometimes across multiple sensory modalities, including visual and  auditory.

Augmented reality- ●The primary value of augmented reality is the manner in which components of the digital world blend into a person's perception of the real world, not as a simple display of data, but through the integration of immersive sensations, which are perceived as natural parts of an environment. Augmented reality (AR) differs from virtual reality (VR) in the sense that in AR part of the surrounding environment is actually 'real' and just adding layers of virtual objects to the real environment.

●Mixed reality (MR) is the merging of real and virtual worlds to produce new environments and visualizations, where physical and digital objects co-exist and interact in real time. Mixed reality does not exclusively take place in either the physical world or virtual world, but is a hybrid of reality and virtual reality.

✘Unstructured data includes quantitative data that is stored in an organized manner. It consists of numerical and text data. It is easy to analyze and process structured data. It is generally stored in a relational database and can be queried using Structured Query Language (SQL).

-structured data- includes qualitative data that lacks any predefined structure and can come in a variety of formats (images, mp3 files, wav files, etc.). Unstructured data is said to lack “structure”. It is stored in a non-relational database and can be queried using NoSQL.

✘Big data is exactly what the name suggests, a “big” amount of data. Big Data means a data set that is large in terms of volume and is more complex. Because of the large volume and higher complexity of Big Data, traditional data processing software cannot handle it. Big Data simply means datasets containing a large amount of diverse data, both structured as well as unstructured.

- refers to the amount of data that is being collected. The data could be structured or unstructured.

- refers to the rate at which data is coming in.

 refers to the different kinds of data (data types, formats, etc.) that is coming in for analysis.

- refers to the usefulness of the collected data.

- refers to the usefulness of the collected data.

-refers to the quality of data that is coming in from different sources.

Customer experience- is another field that has benefited greatly from the increasing popularity of Big Data. More data means we have larger datasets to train our ML models, and a more trained model (generally) results in a better performance. Also, with the help of Machine Learning, we are now able to automate tasks that were earlier being done manually, all thanks to Big Data.