CHALLENGES TO DATA SCIENCE AND DATA SCIENTISTS

We already know how important data science is in today's era. It is due to this reason that data scientists are considered no less than super humans. But as a data scientist and as a person practicing data science, there are few general problems that you may encounter. It requires a lot of good analytical skills and smart work to overcome these problems and to get relevant information out of the given data. Let us look at a few problems faced by data scientists and the possible solutions which can be opted so that the problem can be gotten over.

The identification of the problem

The first and foremost step to solving a complex problem is determining the various aspects of the problem and to devise a strategy as to how to start with the problem. It is very important because the solution that may come to your mind after reading a problem may not be the most efficient solution. It may be easy to implement let me take a lot of time to do the job and may not be so efficient. So there may be another solution that is difficult to think of and implement but makes the job a lot easier. The solution to the problem is that there must be a proper research over how to make the solution more efficient and less time consuming.

Accessing the appropriate data

For finding the solution, it is very important that we have gathered the right data. It is very difficult to gather the right data from large chunks of multidimensional data. There might be less variety of data or the data may be hidden. The solution to this problem is that we must have better data management systems which can prove useful for filtering and separating similar kind of data.

Cleansing of data

If the data is dirty it would lead to incorrect results. Data scientists have to deal with a lot of data and it is very difficult to clean the data before starting the work. The solution to this problem may be that data scientists should use various data governance tools to ensure increased accuracy and consistency in data and also the data quality should be maintained.

Dearth of expertise in various domains

There are a few software or tools that a data scientist must be familiar with. But in many cases it is found that data scientists are not properly trained and do not have much knowledge. The solution is that data scientists must be good at various domains like business, statistics, etc.

Issues regarding data security

As there is a large amount of data present with a data scientist, and their needs to be some mechanism which ensures the safety of the data so that it is not accessed by hackers who may misuse the data. The solution to this problem is that there must be some system like a firewall that optimizes the traffic on the server so that the data is not accessed by unauthorized people and misused.

From the author's desk

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