Updated June 15, 2023
Difference Between Data Scientist vs Business Analyst
Data plays a significant role in the growth of any business exponentially. For the data to be understood with its trends, it requires lots of analysis and research. It requires special skills which help in understanding the data pattern and coming to a conclusion about how the data will lead to the business’s growth and how changing functionalities will bring in the necessary change. Data scientists and business analysts mutually do this job. Though both these roles help expand any field, Data Scientists vs Business Analysts have roles and responsibilities which differ in their ways. Let us understand the differences between a data scientist and a business analyst. Although the main motto of both jobs is business growth, the variance in their actual work will be seen further.
Head-to-Head Comparison Between Data Scientist vs Business Analyst
Below are the Top 5 differences between Data Scientist vs Business Analyst:
Key Differences Between Data Scientist vs Business Analyst
Though both these roles seem to have a similar difference between Data Scientist and Business Analyst differ in the following ways:
- A data scientist needs to analyze large amounts of data and should be able to manipulate and make necessary changes using mathematical and statistical operations. They also need to discover new patterns and make future predictions. They must have technical knowledge and know languages like Python, R, etc. On the other hand, business analysts must know end-to-end business. They should understand the impacts of changes with it and try to bring out changes that will increase customer and employee productivity. They should collaborate and constantly communicate with stakeholders and clearly understand their needs. They must also help design the IT system from a business point of view and coordinate with them.
- The need for data scientists arose when we had an ever-increasing demand for synchronization between data and the IT industry. All departments in a company require a data analyst these days. They provide a sophisticated analysis through their programming expertise and without waiting for inputs from the IT industry. They need data, and they can go ahead with their research which will bring the organization to a new competition level and also unfold hidden trends and patterns, which will help the organization lead in the market. Business Analysts are needed to bring a change in the existing functioning of the business. They must analyze the current practices and bring a change that will be more effective and profitable to the organization. They should come up with questions for project customers, end users, and subject matter experts. Next, the total requirements that are gathered must be documented with the definition and need for the change. Business analysts are the ones who bring precision to estimates in the project schedules.
- The duties of data scientists involve data visualization, where they need to explore the data and find hidden details from the data, which will reveal the current trends and help them model patterns which in turn help in predicting future recommendations. They must be well-versed in machine learning and data mining, which will help build analytics applications for high profits in the market. They must communicate technical findings to sales and marketing teams. A business analyst must identify stakeholders and analyze and document the requirements. They must evaluate the proposed solutions and share them with all stakeholders. Once that is done, they will execute the changes with a development team and follow up with deadlines. They are also expected to conduct user acceptance tests and gain acceptance from a client. After this, they are also responsible for creating user manuals and final documentation.
- The main tools that a data scientist uses are data warehousing, data visualization, machine learning, and languages like Python, R, and SQL. On the other hand, business analysts have commercial software like iRise, Jama, and BitImpluse, which help provide solutions across different industries.
Data Scientist vs Business Analyst Comparison Table
Following is the comparison table between Data Scientist vs Business Analyst
| Basis for Comparison | Data Scientist | Business Analyst |
| Basic Difference | Data Science is all about discovering new things, a revelation of new data that will solve complex problems. Finding conclusions through statistics through mere observation and gradually reaching the perfect optimized solution is the job of a data scientist. | Business Analysts are a platform between IT and business stakeholders. They need to have the deep business knowledge and be involved in demanding questions to get value for money and bring value to developments done in the IT industry. |
| Requirement | A data scientist needs to know all the latest tools, SQL; if required, they may need to code. They should have in-depth knowledge of mathematics and statistics. | Business analysts may not require any technical knowledge. They must be comfortable assessing changes, developing business cases, and defining new requirements or changes in a project from the functional perspective. |
| History | Data analysis seems to be a new rage; it dates back to 1962 when John Tukey wrote about ‘The Future of Data Analysis. Post that, there were mentions about this, and it started trending from 2006 through 2011 till now, where data scientists are the most sought job profiles. | Business Analysts came to the rising in the 1970s when they started documenting all manual processes. They found the need to automate repetitive tasks, identify problems and deliver good-quality technology at the expense of business needs. Through the 1980s, Business Analysts evolved to support business goals and mediate between IT and business resources more effectively. |
| Responsibilities | A data scientist has to handle and extract large amounts of data. This requires in-depth knowledge of SQL to segregate datasets. They must have advanced knowledge of machine learning to make changes in data by themselves and get a deeper insight. | Business Analysts need to gather and prepare requirements. They must prepare documents and also analyze and model all criteria. Post analysis, they must take over the required changes and convey them to the IT team. Once changes are done, they must perform acceptance testing to check if the requirements are met. |
| Tools | The tools of data scientists are none other than Data warehousing, Data visualization, and machine learning. | There are various tools for business analysis, like Blueprint, Axure, Bit impulse, etc., which make improve productivity. |
Conclusion
Thus, both of them perform the job of increasing the value of a business. The different roles and responsibilities they perform help an organization know its value and provide a way of improving and increasing its market value. The process improvements by business analysts and the predictions done by data scientists assist the company in having a safe present and a bright future.
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