Advantages and Disadvantages of Data Science

In today’s world, data is generated at an alarming rate. Every second, lots of data is generated; be it from the users of Facebook or another social networking site, or from the calls being made, or the data generated from various organizations. How to handle such an incredible amount of data has become a concern for people around. So 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 analyze, understand, process and extract the information from the structured as well as unstructured data. Understanding and processing data is generally done by two groups: the first being the data scientists and the second the analysts.

The data scientists are involved in the root level, where they work on the database to obtain information and help develop the product. These people have good math and business acumen. However, data scientists play an important role in helping to design and develop the product. Their task is to build algorithms, test and refine them, and finally implement in the production system.

On the other hand, analysts play different types of roles, be it a financial analyst or a market analyst or whatever. They analyze the data and gain insight into what information the data is trying to convey.

However, it should be noted that data science and data analysis are completely different topics. One must not confuse data science with data analysis, since data science is considered a box for tools and methods, data analysis is considered as chambers in the box.

When talking about the benefits of data science, a few points are listed below:

1.) The developed products can be delivered in the right place and at the right time, because data science helps organizations know when and where their products sell best.

2.) It helps the sales and marketing team of different organizations understand their audience and it helps to customize the customer experience.

3.) It also helps an organization make faster and better decisions that lead to improved efficiency and higher profits. It helps identify and refine the target audience in different organizations.

4.) It has made it relatively easier to sort data and look for the best candidates for an organization. Big Data and data mining have made the processing and selection of resumes, aptitude tests and games easier for the recruiting teams.

It also has some drawbacks:

1.) The information obtained from the structured or unstructured data can be abused against a group of people in a country or committee.

2.) The tools used for data science and analysis can cost an organization a lot as some of the tools are complex and require people to undergo a training to use them.