What Are the Differences Between Data Science & Big Data?

Data is the king, and most of the companies are relying on this to create strategies for their growth and gaining an edge over their competitors. As per IBM, in 2012, around 2.5 billion gigabytes of data were created. This number has grown steadily since then. There has been huge growth and reliance on data science and big data. The latter two are being worked on, and many companies are now looking for Big Data experts and Data Science experts. Many people confuse the two terms, but these are different aspects of data that has a different approach. 

How is big data different from data science?

If you are planning to learn more about data science or big data, it is important that you must know how they are different.

Data Science- It is a field that involves the use of different statistical tools like statistics, data cleansing, mining, and programming to prepare and along with big data for better analysis such that meaningful insight can be deciphered from it.

Big Data-  It is the collection of data that comes from different sources in different formats. You can use it for analyzing the insights which can help in better decision making.

Tabular representation of the difference between Big Data and Data Science: 

Nowadays, companies are looking for specialized skills in different fields so that they can use this data to derive a conclusion, which can eventually help in the growth of their business. If you are also willing to learn about Big Data and Data Science, then Global Tech Council is offering a certification program in Big Data certification and Data Science certification. After successful completion of this program, you will become eligible to get a good-paying job across different industries.