Being a less-saturated, high paying field that has revolutionized several walks of life, it also has its own backdrops when considering the immensity of the field and its cross-disciplinary nature.
While Data Science is a field with many lucrative advantages, it also suffers from its disadvantages.
- Mastering Data Science is near to impossible :
Being a mixture of many fields, 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.
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.
2. Large Amount of Domain Knowledge Required :
Another disadvantage of Data Science is its dependency on Domain Knowledge. A person with a considerable background in Statistics and Computer Science will find it difficult to solve Data science problem without its background knowledge.
3.Arbitrary Data May Yield Unexpected Results:
A Data Scientist analyzes the data and makes careful predictions in order to facilitate the decision-making process. Many times, the data provided is arbitrary and does not yield expected results. This can also fail due to weak management and poor utilization of resources
4. Problem of Data Privacy:
For many industries, data is their fuel. 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 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.