Major challenges faced in data science

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Date sent: 2020/06/29 12:38:49
Data science is spreading in every region of the world at a rapid rate. It is the most trending career option that every student is looking forward to. Data science is not as simple as other career options. It faces many difficult challenges. So in this article, I will discuss the different challenges that occur in data science.

Identifying the main issue

In data science, the most difficult challenge faced by the data scientists is identifying the major issues in the data. The job of the data scientist is to understand the given data and also to make it simple so that it can be explained to the common people. The insights made from the analysis of those data should eliminate the major errors and glitches from the data. Data scientists often use dashboard software which provides many visualization widgets that helps in making the data simple and meaningful.

Data Quality

Deep learning and machine learning are so powerful that they can easily outrun human intelligence. Algorithms in machine learning do the things that are taught to them, but the problem arises when the data is not curated properly. Machine learning algorithms have the extreme power to learn different things rapidly, but they can only execute those things that they are programmed to execute. So the data should be properly curated and data scientist faces an uphill task to curate those data.

Data Quantity

The development of a strong model is the top priority for the data scientist. A difficult problem requires a very intense model with important model parameters. So, if there are more amounts of model parameters, more amount of data is required. It is also very difficult to get quality data for training such models. Even unsupervised algorithms require a humongous amount of proper data to have a meaningful output.

Multiple sources of data

Big data helps the data scientist to reach a wide and vast scope of different data software and platforms, but the data scientist faces a huge problem in handling those data. There is a solution to this problem; the solution is using digital data warehouses that can connect different data from various locations by using cloud-based data platforms. Useful conclusions and insights can be extracted if the total reach of the given data is deep.


Sometimes, there are many unexpected results or outputs that are obtained which might not be the proper output that is desired by the data scientist. In this type of challenging situation, data scientists pressurize supervised understanding and learning for future explorations, selection of models, and proper selection of algorithms. With more power and time, a data scientist can produce models of great predictive strength with very little interpretation.

Common challenges

The most common challenges that the data scientist faces are dirty data, politics in the company, lack of proper and clear questions, explanation of the data science concepts in business languages, the data provided cannot be accessed or Inaccessible.

Resource box

If a person thinks that data science is the field where he or she can continue their career and can invest on, then 360DigiTMG is the best option a person can take. It provides the best Data Science Course which will definitely help the pursuer.

Date sent: 2020/09/19 08:21:43
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