How data analysis is disrupting the engineering sector. (B.Tech computer science in Data Analysis)

Data is a major component in today’s world. Every business, whether it is technical or non-technical, small scale or enterprise or a start-up, depends highly upon data.

B.Tech in computer data science is a new, exponentially growing field which consists of a set of tools and techniques used to extract useful information from data. The program deals with data Science as an interdisciplinary, problem-solving oriented in which students learn to apply scientific techniques to solve practical problems. Apart from being less saturated, a high paying field and a lucrative career option, B.Tech in computer science also has quite a few drawbacks while considering the immensity of the field and its cross-disciplinary nature.

Some of the disadvantages are as follows:

Not economical

Data science is quick and inexpensive for simple engineering methods. It’s quite useful for baseline development. However, it is relatively expensive for more sophisticated engineering models. It needs to be calibrated with insight data. Data science is not a good option for evaluation of spillover. The tools used for data science and analytics can cost a lot to an organization as some of the tools are complex and require people to undergo training in order to use them.

Lack of privacy

Data is the fuel of many industries. Data Scientists help companies make data-driven decisions. However, the data utilized in the process may breach the privacy of customers. The personal data of clients such as purchases, online transactions, subscriptions are visible to the parent company and may at times cause data leaks due to lapse in security. The ethical issues regarding preservation of data-privacy and its usage have been a concern for many industries. The companies may exchange these useful customer databases for their mutual benefits.

Misuse of information

The information obtained from the structured or unstructured data using data analytics can also be misused against a group of people of a certain country or community or caste.

Excess amount of information is required

It becomes difficult for a Data Scientist from a different background to gather information about a specific domain. This also makes it difficult to migrate from one industry to another.  A person with a considerable background in Statistics and Computer Science will have a hard time-solving Data Science problem without its background knowledge.

Difficult to master

Data Science stems from Statistics, Computer Science and Mathematics. It is far from possible to master each field and be equivalently expert in all of them. Data Science is an ever-evolving field that will take years to gain proficiency. While many online courses have been trying to fill the skill gap that the data science industry is facing, it is still not possible to be proficient at it considering the immensity of the field.

These disruptions can be overcome beforehand during the theoretical study by training the aspirants in such a manner that they are already aware of the disruptions and they are trained how to deal with them. At AP Goyal Shimla University, we aim to create such situations where the students are exposed to the possible disruptions and they themselves discover the ideal ways to deal with the issue. Hence we work towards enhancing the problem-solving skills among the students in order to produce efficient professionals. Here at APGSU, we strive for excellence in the form of framing structured thinking, analyzing business problems, data visualization, connecting data using SQL.

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