Data Scientist vs Business Analyst

Data Science is way bigger than Business Analytics and considers several factors that Business Analytics doesn’t even think of. While Business Analytics just focuses on business-related issues, Data Science even digs into the influence of factors like weather, customer preference, and several seasonal factors.

Let’s understand the differences between the two on a professional level, i.e. the differences between a Data Scientist vs. a Business Analyst.

Roles and Responsibilities:

Roles and Responsibilities of a Data Scientist include extracting and organising data. They draw meaningful insights from that data which could be structured or unstructured. To do all of it, they must have good knowledge of Machine Learning, Statistics, Probability, and other mathematical skills. Furthermore, they must have a firm grip on concepts like Python, R, Spark, Hadoop, and Tensor flow.

The roles and responsibilities of a Business Analyst include communicating with clients and providing them with business solutions. They must have great interpersonal and management skills to assist clients in designing and implementing relevant technical solutions. Along with all the assistance, they are always on their A-game in monitoring the overall business growth.

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Career path – The future

No matter what the sector is, be it healthcare, finance, management or transportation, the data needs to be taken care of and insights must be taken from that data for that industrial segment to grow. So, to make sure this happens, companies are looking for experts and no doubt Data Scientist is one of those job roles that are in most demand today and are one of the highest paying jobs in the world. The demand for Data Scientists is not going to reduce anytime soon considering the rapid production of granular data across the globe. 

Business Analyst is one of those jobs that report a great level of work-life balance and job satisfaction. Again, it is one of those job roles that have a lot of openings in the market and one of the well-paid jobs too. Business Analysts are in great demand among organisations that are looking forward to scaling their businesses and improving their overall performance. The best part is the role of a Business Analyst is not limited to one designation, it changes from company to company. There are several roles that you can pursue if you have expertise in Business Analysis like Network Analyst, Project Manager, Data Analyst, and Business Consultant.

Skills required

Skills required to be a Data Scientist include: 

Python – Data Science requires a firm hold of programming languages. When it comes to programming in Data Science, Python is one of the most widely used programming languages as it is easy to use and highly adaptable, even for people without a coding background.

Keras – Keras is used for artificial neural networks as they provide a python interface. Hence, they are used when it comes to experimentation with neural nets, that too at a great speed. 

PyTorch – PyTorch is another deep learning framework extremely popular for its agility and compatibility with the Python framework. The framework simplifies the overall process to create an Artificial Neural Network (ANN). 

Computer Vision – Computer Vision enables the Data Science systems to extract knowledge from images and videos to make necessary decisions. 

Deep Learning – Deep Learning is something that makes the entire Data Science system more accurate as it enables the creation of extremely complex models.

Natural Language Processing – Natural Language Processing or NLP is something that is bridging the gap between Data Science and humans, by teaching computer systems how to read and interpret like humans. 

Problem-solving – Problem-solving just doesn’t refer to the problem that is in front of you, being a Data Scientist you are responsible for solving problems that may be hidden.

Analytical Thinking – Data Scientists must have an eye for detail and analyse problems before actually starting to deal with them. It is important to examine the problem from all verticals and then reach an effective conclusion. 

Skills required to be a Business Analyst include: 

Programming skills – Programming Skills are not a must for a Business Analyst, but having some is always a plus. For example – knowledge of R and Python can help you in a quick and effective analysis of data.  

Statistical analysis – Business Analysis requires a good knowledge of statistics and knowledge of different statistical methods to interpret real-world situations.  

Business Intelligence tools – Business Intelligence or BI tools enable you to understand different trends and insights from business data, which is important to make impactful decisions. 

Data mining – Data mining is one of the important skills of Business Analysis as it is about digging relevant information from chunks of data. So, companies use software to look for patterns and graphs in data and make relevant business decisions accordingly.

Analytical problem-solving – Business Analysts are about solving issues coming from customers or other stakeholders, so having the skill of analytically solving problems is a must. 

Data visualisation – To make any important and accurate business decisions, the first and foremost step is to visualise or examine data chunks to understand market trends and loopholes.

 Type of Data

Data Scientists work on both structured and unstructured data to fetch insights from huge chunks of data.

Business Analysts are just concerned about the structured data. They work on that data with several Business Intelligence tools to draw insights. 

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