There is a reason behind all the accolades this course is getting from top universities and the business world. The reason is simple: this is the information age. Data is paramount in today’s life. Useful insights can be extracted from the data collected through online social networking sites and call centers etc. However, not all data is useful and is called dark data which is redundant in nature and can be ignored. It does not provide any useful information to companies about customers.

Big Data, the term simply means a large amount of data existing in the system that has significance and can make predictions about the future. Big data can be classified into three categories:

Descriptive analytics:

You are describing the data as it is. Plotting points according to the understanding and critical analysis of the data. Discovery about facts and figures is cited as such and the analysis is done at the level of the information collected.

Predictive Analytics:

This form of analysis is carried out due to the knowledge discovered and decisions are made on the basis of it for one or another type of project. This information becomes the driving force to become beneficial and crucial in the whole process on the target market. Having past data and reflecting on it with the help of mathematical tools and statistical tools gives an edge in predicting things.

Prescriptive analytics:

Such analysis is done when there are some things that require changes. Undertakes and analyzes a series of options and then determines the best route for the project to be undertaken. This type of analysis is adapted to companies that want to be profitable in their operation and remain positive about the results of the project.

Machine learning:

Machine learning is also of paramount importance in data science. Without this, it is useless. It is the prerequisite that allows a project to be carried out successfully. Various languages ​​are being taught during data science like Hadoop, Python and others. Machine learning allows apps like Siri to provide better results to the person requesting things, as they are designed to identify patterns. It’s this machine learning working in the background. The more precise you are, the better the results.

Things like data science is something that is naturally evolving. With the upcoming IoT concept, things have become different. The application of data science has become even more important because this knowledge is absorbed by the normal life electronic devices that people use. Recording the number of steps a person traveled in a day on a watch to analyze an individual’s health based on a month’s worth of data is all that data science is making possible. Things are changing fast in this world and structured data is given importance. Surely, this field will never become redundant in the days to come.