The world today is rapidly digitalizing, and as it does there has been a great expansion in the area of virtual reality. Social media and the World Wide Web make for an integral part of people’s lives, and people today have been making the most use of digital technology since its inception. With the modern age technology a lot of things have changed. People no longer choose things the way they did earlier. This is one of the reasons why businesses today face a huge challenge. It is an accepted fact today that everything from services to products has gone virtual, this being said it is now a task for companies to try and sell in the virtual sphere.
Recently there has been the inception of a solution for these woes of the businesses and firms. Now it is very much possible for companies in various industries to expand their revenues through this very solution. Data Science has been the key to the development and growth of various businesses. It came to the fore very recently and in simple terms can be called the science of data. Today, one a daily basis there are millions of people either surfing the net, purchasing something, getting a service delivered to them and so on. This activity on the World Wide Web then takes the form of records, in simpler terms there is a combined history of all of the world’s browser history.
Data Science is a field which deals with this huge tsunami like data, its structuring, analyzing and finally deriving value information from it. Professionals working in the field of Data Science usually are assigned with the responsibility of extracting the data, structuring it, drawing insights and then presenting it in the form of value decisions that help the businesses to proper. It basically is advancing the age old traditional system of analyzing data sets manually with the help of tools, algorithms and softwares.
Data Analytics and Data Analysis are the various functions that come under the umbrellas term that is ‘Data Science’. Someone who deals with analytics of data would be an expert at extracting data, data mining, structuring it with the help of various tools like R programming, SAS programming, Python, Pig and so on. After this is done, the professional would go onto visualize the data and put it in a way that it could be accessible for anyone to interpret.
Data Analytics is more technical in nature, whereas Data Analysis is presumptive and predictive. A professional working here would have all the qualities of someone in the data analytics industry. It is important to know, that a Data Analyst knows more than a Data Analytics professional. These are people who have the knowledge of programming, are great statisticians and can derive great insights from the data. They are also equipped with skills, which enable them to see the data in the most abstract way and know what others don’t know about it.
Although it does seem like Data Analytics holds lesser importance than Data Analysis, but it is true that these terms still need to be defined more clearly. Another fact that is more important to know is that, a Data Scientist is someone who needs to be equipped in both of these fields. This is one of the many reasons why, these professionals are the most sought after. Today, there are many institutes which offer courses in Data Analytics as well as Data Analysis as well as the various tools like Python, Big Data Hadoop and so on.