Data science is essentially the study of data. It involves developing efficient methods, systems, and algorithms for recording, analysing, and storing of data – structured as well as unstructured – to extract relevant knowledge and insights.
Data mining is simply the process of gathering information from data – structured and unstructured – and converting such data into one form, which is easily available to users for analysis.
Data analytics essentially covers the techniques of analysing data, and includes algorithms and other processes of data mining. These techniques help in identifying which method yields quicker results and is more efficient.
Data analysis is basically about the processing and analysing of stored data. Such analysis can enable accurate predictions that can be of help to the society. It helps data scientists understand the requirements of people and drive sales.
Machine Learning is not entirely related to Data Science, but it can greatly help in the process. Machine learning, as the name suggests, is essentially helping machines learn from different data. It helps machines convert data into a language that machines can easily understand. It forms an integral part of Artificial Intelligence, and is hence one of the most intriguing aspects of data science.
As is evident from the name, Big Data literally means a huge amount of data – structured, semi-structured, and unstructured – collected by companies to be used for analysis. It includes a tremendous amount of audio files, video files, text, and numbers. For example, all data generated by social media, internet networks, banking, etc.