In today’s world, data is being generated at an alarming rate. Every second, lots of data is generated; be it from the users of Facebook or any other social networking site, or from the calls that one makes, or the data which is being generated from different organizations. How to handle such an incredible amount of data has become a concern for people around. So in order to understand and manage this huge amount of data, data science has come to our rescue.
Data Science is a combination of the following skills: Mathematics expertise, business/strategy acumen and technology and hacking skills.
It helps us in analyzing, understanding, processing and extracting the information from the structured as well as unstructured data. Understanding and processing of data is generally done by two groups: first being the data scientists and the second are the analysts.
The data scientists are involved in the root level where they work on the database to obtain information and contribute in developing the product. These people have good mathematical and business acumen abilities. However, data scientists play a vital role in helping to design and develop the product. Their task is to build algorithms, test and refine them and finally deploy into the production system.
The analysts on the other hand play different types of roles, be it that of a financial analyst or a marketing analyst or whatsoever. They analyze the data and gain insights as to what information, the data is trying to convey.
However, it should be noted that data science and data analytics are entirely different topics. One must not confuse data science with data analytics because as data science is considered to be a box for tools and methods, data analysis is considered to be the chambers in the box.
Talking about the advantages of data science, a few points are listed below:
1.) The developed products can be delivered at the right place and at the right time because data science helps organizations in knowing when and where their products sell best.
2.) It helps the sales and marketing team of different organizations to understand their audience and it helps in personalizing the customer experience.
3.) It also helps an organization in making faster and better decisions which lead to improved efficiency and higher profit. It helps in identifying and refining target audience in various organizations.
4.) It has made it comparatively easier to sort data and look for best of candidates for an organization. Big Data and data mining have made processing and selection of CVs, aptitude tests and games easier for the recruitment teams.
It has some disadvantages as well:
1.) The information obtained from the structured or unstructured data can be misused against a group of people of a country or some committee.
2.) The tools used for data science and analytics can cost a lot to an organization as some of the tools are complex and require the people to undergo a training in order to use them.
Shalini M