Why is data science so hard? This is a question that we often get asked here at Guttulus and we often are at crossroads because we don’t really consider data science to be too difficult although we appreciate the fact that some people find it challenging.
To help address the question of why data science is so hard to some people, we have taken a look at the building blocks of data science and mistakes that people make when getting into data science. With the help of our CEO here at Guttulus, we have put together a list of some of the reasons why most people find data science to be hard and we hope this list will help make your life debuting into data science much easier.
Here are some of the reasons why some people find it hard to get into data science:
Tips Why Data Science is Hard
Data Science Needs a Mathematics and Statistics Background
Mathematics and statistics are not everyone’s cup of tea. Unfortunately, these two are very essential in data science and one needs to have a good understanding of the subjects if they are to study data science. People who don’t have an understanding of calculus, geometry, statistical methods and probability, will always consider data science to be difficult.
Data science needs computer science knowledge
You can’t get into data science if you don’t have some basic knowledge in computer science. You’ll need knowledge in algorithms, programs, data analytics and other computer science aspects for you to get into data science. People who don’t enjoy computer science and dread algorithms, will always find data science to be a big challenge.
Machine learning is very sophisticated to some
The other reason that some people consider data science to be a challenge, is the fact that one needs proficiency in machine learning which in itself is not a walk in the park! You will need to understand the basics of machine learning and venture into deep machine learning before you can be considered a good data scientist and not everyone enjoys machine learning.
Handling databases is not very easy
Data science requires knowledge on how to handle databases. Handling databases requires thorough training and practice before one becomes proficient enough. Unfortunately, most people struggle with databases and this is why they consider data science as a whole to be very difficult.
Knowledge in programming languages is a requisite in data science
You will need some form of knowledge in programming languages such as R, Python, Java and Scala if you are to make it in data science. Forget learning one language, learning multiple programming languages and applying it daily becomes a real hassle for a lot of prospective data scientists.
Troubleshooting code is the other difficult aspect of data science
Troubleshooting code and trying to identify mistakes, is not very easy. You will need years of learning, practicing and developing functional software before you can become prolific at troubleshooting code. People who dread troubleshooting after coding, will always regard data science as a difficult profession.
Data scientists need knowledge in business administration
You can’t define business problems and communicate the insights drawn from the data that you have analyzed if you aren’t proficient in business administration. People who are not as good in business administration are therefore bound to struggle in the field of data science.
Understanding the ever dynamic analytical tools is very difficult
To make it in data science, one needs to understand how the data analysis tools work. This is not made any easier by the fact that the modern day data analysis tools are very dynamic and keep on changing. One will therefore need to train on a regular basis to ensure that they are equipped with the skills necessary to use the analytical tools.
Combining all the above is very difficult
To become a professional data scientist, you will need to combine all of the above factors and use them all at once, is one hell of a difficult task. This is why it is very difficult to come across a complete data scientist with all of the above mentioned skills. Complete spectrum data scientists are hard to come by which only confirms the fears of many regarding the difficulty of data science.
Some people get into data science for the money and not out of passion
The other reason why people struggle in data science, is the fact that they get into it just for the money and not because they are passionate about it. As a result, they end up struggling to even grab the most basic of concepts needed to survive in data science.
Get into data science if you are ready to sacrifice and dedicate time to learn and earn most of the above mentioned skills. By so doing, you will not struggle with data science and will find it enjoyable and easy.
Talk to Guttulus today on data science
Want to get started in the world of data science and why it’s not all too difficult? Give us a call today here at Guttulus and we will gladly be of service to you. To keep up with the trends in the world of data science, subscribe to our mailing lost and constantly read our blog and you will never miss a thing about data science.