Data Scientist vs Business Analyst – 5 Core Aspects to Choose Your Career
Data Science and Business Analysis are two of the most recurring terms in the industries. Like data scientists, business analysts also deal with data. However, their methods of dealing in data and their use cases are different. Furthermore, their roles and responsibilities are also different. In this article, we will discuss Data Scientist Vs Business Analyst on the basis of skills, responsibility, salary, and tools used by them.
Industries need data to progress and generate insights about data related problems. There are various data related occupations that address the growing need to evaluate data. Two of the many such occupations are that of Data Scientist and Business Analyst. While both of these fields revolve around data, their operations vary. Here, we will see how these operations vary and how they are utilized by the industries.
What is Data Science?
Data Science is high in demand. It has become a buzzword of the 21st century. Data Science is a discipline that involves the extraction, preparation, analysis, visualization, and maintenance of information. Data Science is a cross-disciplinary field as it stems from mathematics, statistics and computer science.
With the massive increase in data, there is a pressing need to analyze such a large volume of data. With Data Science, you have the ability to not just manage such a large volume but also develop machine learning models that predict future outcomes. These machine learning models are beneficial for forecasting business growth and analyzing future outcomes.
Currently, there is a dearth of data science roles. The number of positions in Data Science has grown by 650% since 2012. Furthermore, the United States Bureau of Labor Statistics predicted that there will be 11.5 million jobs in data science by 2026.
What is Business Analysis?
Business Analysis is a process that deals with analyzing data and deriving insights about business operations. Business Analyst makes use of several tools, applications, and methodologies that help the managers to make informed business decisions. A business analyst employs quantitative techniques to investigate the performance and health of the business.
A business analyst makes intensive use of statistical analysis techniques, such as exploratory analysis and predictive analytics. Moreover, a business analyst is required to understand the outcome of various business decisions through statistical analysis. As a business analyst, you are required to perform exploratory data analysis, where you are required to visualize the data in form of graphs to provide insights to the business team.
There are various tools that a business analyst utilizes, but the most popular of these tools is that of business intelligence. These tools help companies to take careful risks and make data-driven decisions.
Companies shape their strategies based on the insights provided by the business analysts. Some of the areas where the companies benefit through business analysts are:
- Companies are able to perform data mining on large datasets, that helps them to explore patterns and find new relationships.
- Companies derive results through an in-depth statistical and quantitative analysis of data.
- Business Analysts perform tests on previously taken decisions through A/B Testing and multivariate testing.
- Companies use predictive modeling and analytics to forecast future results.
Summarizing all the above points, a business analyst basically makes the businesses grow. They are well versed with various statistical tools and methodologies that enable them to take far-sighted decisions and formulate business strategies.
Data Scientist vs Business Analyst
In this section, we will discuss Data Scientist vs Business Analyst through their skills, responsibilities, and various tools utilized by them.
1. Data Science Vs Business Analysis – Definition
Data Science is the ocean of data operations. It is an umbrella term that incorporates all the domains that involve data to be processed in some or the other form. Data Science is the bigger set whereas business analysis occupies a subset of it. A Data Scientist deals with not only the analysis of data but also developing predictive models that use machine learning algorithms to find the outcome of events. Furthermore, along with statistics, Data Science makes use of programming. The role of a data scientist is not only limited to business but also various other domains like health, manufacturing, finance, and transportation.
Business Analysis, on the other hand, uses data and quantitative measures to gain new insights about the business. Using various statistical methods, business analyst measures and understands the performance of the businesses. It is closely related to management science. This is because business analysis focus on unearthing new insights, understand the underlying business performance and use fact-based management for decision making. Business Analysts drive the economy of businesses and facilitate their growth in the market.
2. Data Scientist Vs Business Analyst – Responsibilities
Responsibilities of a Data Scientist are –
- Data preprocessing which involves data cleaning and data transformation.
- Developing predictive models that forecast the outcome of future events based on historical data.
- Fine-tuning the machine learning models and optimizing their performances.
- Formulating new questions that need to be solved by the company in order to take better decisions.
- Using interactive story-telling to communicate results with the team.
Responsibilities of a Business Analyst are –
- Assist the businesses in implementing technology solutions through the determination of project requirements.
- Business Analysts are responsible for quantifying the scope of the businesses. Business Analysts communicate with their team, consumers and the stakeholders to formulate the vision for the project.
- S/he communicate their plan and findings with the team and with their stakeholders. They discuss the project status, application requirements as well as predicted growth of the business.
- A business analyst also determines the functioning of the project. He is required to evaluate both the functional and non-functional requirements of the project.
- Ensuring the satisfaction of the customers is one of the major responsibilities of a business analyst.
3. Data Scientist Vs Business Analyst – Skills
Following are the skills required by a Data Scientist –
- Thorough knowledge of statistics and other important mathematical concepts
- Experienced with various tools like Python, R, SAS etc.
- Should have the right expertise to deal with both structured and unstructured data.
- Well versed with SQL and NoSQL.
- Knowledge of Machine Learning algorithms is a must.
- Possession of Big Data tools like Hadoop, Mahout, and Spark will increase the value of data scientists
Following are the important skills for Business Analyst –
- Possession of a strong suit of communication skills.
- Should be well versed with the concepts of systems engineering.
- Have knowledge of modeling techniques and methods.
- Ability to develop business cases.
- Should possess knowledge of tools like MS Excel, MS Visio, SWOT, Trello etc.
- Possess strong leadership skills.
4. Data Scientist Vs Business Analyst – Tools Used
Popular tools used by the Data Scientists are –
- SQL (MySQL, Oracle PL/SQL)
- Big Data Tools (Apache Hadoop, Spark)
- NoSQL (Cassandra, Redis)
Popular tools for Business Analyst-
- Microsoft Excel
- Board BEAM
5. Data Scientist Vs Business Analyst – Salary
According to Glassdoor, a Business Analyst earns an annual income of $69,163/yr. Whereas, a Data Scientist earns an annual income of $117,345/yr.
In this article, we went through all the details of Data Scientist Vs Business Analyst. We understood their individual definitions. Then, we delineated their roles and responsibilities. Furthermore, we described the skills required for the job and the salary earned by the data scientists and business analysts. Now, you can easily choose your career. You can also follow these steps to become a Data Scientist.
We hope that with this article, you have understood the key differences between Data Scientist and Business Analysis. Drop your queries and feedbacks in the comment section.