Advantages and disadvantages of data science

In today’s world, data is generated at an alarming rate. Every second, a lot of data is generated; whether it’s from the users of Facebook or any other social network site, or from the calls that one makes, or the data that is generated from different organizations. How to handle such an incredible amount of data has become a concern for the people around us. So to understand and manage this vast amount of data, data science has come to our rescue.

Data Science is a combination of the following skills: math background, business acumen/strategy, and technology and hacking skills.

It helps us analyze, understand, process and extract information from structured and unstructured data. Data understanding and processing is generally done by two groups: the first is data scientists and the second is analysts.

Data scientists are involved at the root level where they work on the database to gain insights and contribute to product development. These people have good math skills and business acumen. However, data scientists play a vital role in helping to design and develop the product. Your task is to build algorithms, test and refine them, and finally deploy them to the production system.

Analysts, on the other hand, fill different types of roles, whether it be that of a financial analyst or a marketing 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 analytics are completely different topics. Data science should not be confused with data analytics because since data science is seen as a box for tools and methods, data analytics is seen as the chambers of the box.

Speaking about the advantages of data science, a few points are listed below:

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

2.) Help the sales and marketing team of different organizations understand their audience and help personalize the customer experience.

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

4.) It has made it comparatively easy to sort through data and find the best candidates for an organization. Big Data and data mining have facilitated the processing and selection of CVs, aptitude tests and games for selection teams.

It also has some disadvantages:

1.) Information obtained from structured or unstructured data can be misused against a group of people from a country or some 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 be trained to use them.