Data science and Data analytics are growing at an enormous rate and companies are now looking for professionals who can swift through the goldmine of data and help them drive swift business decisions efficiently. Big data has become a major component in the tech world today. The concept of big data has been around for years most organizations now understand that if they capture all the data that streams into their businesses, they can apply analytics and get significant value from it. However, the creation of such large datasets also requires understanding and having the proper tools on hand to parse through them to uncover the right information. To better understand big data, the fields of data science and analytics have gone from scratch to becoming essential component of Business Intelligence and big data analytics tools. 

What is Data Science?

Data Science is a detailed study of the flow of information from the colossal amounts of data present in an organization’s repository. It involves obtaining meaningful insights from raw and unstructured data which is processed through analytical, programming, and business skills. The main goal is to ask questions and discover potential methods of study, with less concern for specific answers and more emphasis placed on finding the right question to ask. Experts accomplish this by predicting potential trends, exploring disparate and disconnected data sources, and finding better ways to analyze information.

What is Data Analytics?

Data Analytics the science of examining raw data to conclude that information. Data Analytics involves applying an algorithmic or mechanical process to derive insights and, for example, running through several data sets to look for meaningful correlations between each other. The field of data and analytics is directed toward solving problems for questions we know we don’t know the answers to. Data analytics finds answers to the existing set of questions. More importantly, it’s based on producing results that can lead to immediate improvements. Data analytics is also known as data analysis. 

Difference between Data Science & Data Analytics:

Data science is the study of where information comes from, what it represents and how it can be turned into a valuable resource. Data science is all about uncovering findings data through a different process, tools, and techniques involved to identify patterns from raw data. Whereas, Data Analytics, or data analysis, is similar to data science, but in a more concentrated way. The purpose of data analytics is to generate insights from data by connecting patterns and trends with organizational goals. Data Analytics uses basic query expressions like SQL to slice and dice data. The two fields can be considered different sides of the same coin, and their functions are highly interconnected. Data Science is the whole multidisciplinary field that includes domain expertise, machine learning, statistical research, data analytics, mathematics, and computer science. Data Analytics is a significant part of data science where data is organized, processed and analyzed to solve business problems.