Data Science vs Data Analysis vs Data Analytics vs Data Mining vs Machine Learning vs Big Data


Data Science is a cross-disciplinary field that uses scientific methods and processes to draw insights from data. Data Science is about extraction, preparation, analysis, visualization, and maintenance of information. It is an umbrella term with many scientific methods that include mathematics, statistics, computer science, programming and other tools to perform data-operations.

Furthermore, data Scientists deal with the data in order to assist companies in making effective decisions. The companies using a data-driven approach to draw insights with the help of Data Scientists. These insights will be helpful for the companies to analyze themselves and take business decisions according to performance in the market.


According to Gartner, Big Data is a huge-volume, fast velocity, and different variety of information assets that demand innovative platforms for enhanced insights and decision making.

In other words, Big Data refers to the large, diverse sets of information that grow at ever-increasing rates. Big Data solutions provide the tools, methodologies, and technologies that are used to capture, store, search and analyze the data in seconds to find relationships and insights for innovation and competitive gain that were previously unavailable.


Data Analytics refers to the process of examining datasets to draw conclusions about the information they contain. Data Analytics is carried out using Excel, SQL, and R. Data Analyst deals with static data and performs descriptive as well as inferential analysis. They are responsible for testing and rejecting models and hypotheses.

Moreover, they draw insights from the raw information and disclose trends and metrics. There are chances of losing the data in the mass of information. This information helps in increasing the efficiency of a business system.


Data analysis is the process of cleaning, transforming, and modeling data to discover useful information for business decision-making. There are multiple facets and approaches that encompassing diverse techniques for data analysis. Data Analysis plays a very important role in making scientific and helping businesses operate more effectively.


Mining refers to extraction of valuable materials. Data Mining is the process of discovering patterns in the large datasets involving methods of Machine Learning, Statistics, and Database system. It is an interdisciplinary subfield of computer science and statistics which helps in extracting useful patterns and identify relationships.

Data Mining is a complex process that involves intensive data warehousing as well as powerful computational technologies. Furthermore, Data mining also involves the prediction of patterns, calculating predictions, creating information, and clustering the visual data.


Machine Learning is an application of AI that provides system ability to automatically learn and improve the experience without being explicitly programmed. Machine Learning focuses on the development of computer programs that can access data and use it to learn for themselves.

Machine Learning is closely related to computational statistics that focus on making predictions using computers. In addition, the study of mathematical optimization delivers methods, theory and application domains to the field of machine learning.

Author: Aditya Bhuyan

I am an IT Professional with close to two decades of experience. I mostly work in open source application development and cloud technologies. I have expertise in Java, Spring and Cloud Foundry.

Leave a Reply

Please log in using one of these methods to post your comment: Logo

You are commenting using your account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s