Business Analytics vs Data Science: What is the Best Career Path for You?
Knowledge is power, and everyone in the business industry is eager to get their hands on that power. They have often collected an unimaginable amount of data that has the potential to provide them with a wealth of information, but in today’s data-driven society, knowing how to collect data is no longer enough. For businesses and organizations, knowing what to do with the data once they have it is imperative if they want to get ahead in the global economy. Businesses and organizations all over the world are creating more data every day. Data scientists and business analysts are in high demand to help them benefit from and make the most of that data.
What is Business Analytics vs. Data Science?
While business analysts and data scientists are job titles that are often considered indistinguishable from one another, that is certainly not the case. They are both problem solvers and have an advanced skill set that makes them very desirable additions to any business or organization that wants to focus on data to guide their decision making process. However,there are also many differences between the two careers.
Business analysts work within an organization to identify areas of concern that need improvement and then analyze data to help find solutions. They research information to help explain the past and present, as well as predict the future, performance of the business or organization, and then find ways to effectively communicate their findings to their management, colleagues, and other stakeholders. Data drives their decision making process, and improving business or organizational performance is always their primary goal.
There are many different educational paths you can take to be a business analyst. Entry level positions in this field typically require a bachelor’s degree; however, there is not one set major that you must complete. It is a career that requires a wide variety of skills so you may earn an undergraduate degree in any of the following related fields:
- Business Administration
- Computer and Information Science
If you plan to get an undergraduate degree in an area other than business administration, the field that you decide to focus on should depend largely upon the type of skills you think would prove most helpful in the kind of business you prefer to work in.
Most of the candidates for business analyst positions also go on to earn their master’s degree while some complete their doctoral degree as well. When it comes to choosing an area of concentration for pursuing a master’s degree, there is also some flexibility. Recommended areas include:
- Master of Science in Business Analytics
- Master of Science in Information Management
- Master in Business Administration (sometimes with a specialization in Information Management)
- Master of Science in Data Science
Data scientists have a highly specialized set of skills that allow them to look at big problems, dig deeply into them to find a solution, and make a presentation of their findings for others. They use their background in mathematics, programming, statistics, and problem-solving to utilize data in new and creative ways. They work with data in ways that not many can to analyze, cleanse, and prepare it. Then, they come up with ways to convince others of their findings in a presentation that involves connecting stories to the data and explaining it in a way that can be easily understood by people who do not have the same highly technical background. They often use their IT skills to design and develop programming that will help businesses to solve problems. They look for patterns in data and analyze them so they can make predictions of future events and performance.
The educational pathway to becoming a data scientist involves earning a bachelor's degree in one of several possible areas:
- Computer Science
- Management Information Systems
- Technical Communications
- Computer Software Engineering
- Computer Information Systems
- Information Science
Because the skills of a data scientist are so technical and highly specialized, the vast majority, some sources even quote up to 88 percent, go on to earn their master’s degree with 20- 46 percent even going further to also earn their doctoral degree. Many data scientists get their Master of Science in Data Science or Master of Science in Analytics, but you are in no way limited to only those two areas of concentration. Many of the same undergraduate fields of study can also be considered when deciding what to pursue for your master’s degree. Keep in mind the type of business or organization you feel you most want to work in as you make your selection and try to take courses that will deepen as well as expand and diversify your skills as much as possible.
An infographic Business Analytics vs Data Science may prove helpful in further distinguishing between data scientists and business analysts.
What types of skills are needed for business analysts and data scientists?
In order to be successful, people in both careers need to be problem solvers who can understand the needs and concerns of the organizations they work for. They need excellent communication skills so they can work with and explain their findings to others. They need to be critical thinkers and be able to analyze and interpret data. They need to be detail-oriented, organized, and have good time management skills. Both careers require people who have an innate sense of curiosity that drives them to be motivated and persistent enough to dive deeply into problems until solutions can be found.
Business analysts need a strong background in and understanding of the way businesses work. They must be objective and logical as they allow data to drive their decision-making process. They need strong interpersonal skills as they work with others as part of a team. Business analysts need a firm understanding and appreciation of mathematics and statistics. Research skills are key as they spend a great deal of time focusing on problems and trying to come up with innovative solutions. Leadership and communication skills are important as they explain their findings to others and seek to understand the needs and concerns of customers and all of the stakeholders in the business. Some business analysts need computer programming skills as well.
Data scientists need a stronger set of technical and IT skills as they are more deeply involved in computer programming and running experiments on data from the computer. They need strong presentation skills as they are often required to report their findings to groups of people and be able to explain them in much less technical terms. They need to have strong skills in mathematics and statistics and be able to deeply understand the organization they work in. Data scientists have to be able to work with large amounts of data in its current form and then change it into a format that is more easily understood and useful to the business. They need to be able to find stories backed by data that they can share with the stakeholders to increase the likelihood that they will understand their recommendations and choose to follow them.
What types of problems do business analysts and data scientists address?
While the specific types of problems business analysts will address depends greatly on the organizations they work for, there are some common tasks that nearly all of them perform. A business analyst spends a great deal of their time asking questions. This helps them learn more about the business as well as its customers and stakeholders and the needs and concerns they may have. They interview people, conduct internal and external research, and observe the organization at work. This serves to help them better understand any problems and identify possible solutions.
Once they have gathered information, they spend time analyzing it. They look for patterns and trends in data and constantly evaluate it to make sure it is relevant and up to date. Business analysts always try to find the roots of problems and potential solutions.
Business analysts communicate their findings to others, but they also spend just as much time listening. They gain a lot of insight from others that may prove helpful in coming up with the best possible solution.
Documenting their findings in written or visual formats such as charts and graphs is an important part of the job of business analysts. They must figure out the most efficient and effective way to do this in a format that will be clear and easily understood by all involved.
Once a solution has been decided upon, the job of business analysts is by no means complete. They are constantly evaluating the solution to be sure it is achieving the desired outcome and are always open to other possibilities that may better meet the needs of the business.
The types of problems data scientists may face are as varied as the organizations that employ them. They tend to be tasked to solve whatever the organizations view as their most difficult problems worthy of in depth study through data.
Whether it is a matter of tracking social media responses, sales, customer satisfaction, or any of an unlimited list of possibilities, data scientists start by taking the organization’s problem and turning it into a data question. They study it carefully and generate models that attempt to answer the question and make predictions.. They make sure that the data they are collecting is reliable, consistent, relevant, and that the variables that may arise have been controlled so their analysis can be trusted. Once they feel confident in their findings, they come up with stories backed by the data that help them with their presentation to their management, colleagues, and stakeholders.
What are the average salaries for business analysts and data scientists?
Average salaries for business analysts and data scientists are difficult to pinpoint because they can work in such a wide range of different businesses and organizations and even the government. Salaries also depend greatly on the level and type of education they have earned as well as where they are employed geographically. Of course, their official job title and level of experience play a big role in determining salary as well.
Business analysts can expect to earn an average salary in the range of $70,000-90,000 in the United States. The range is larger because the data comes at least partially on the anonymous reporting of their salaries by people employed in the field. As mentioned before, there are also many variables that play a role in determining salary levels.
In New York City, the average salary of an entry level business analyst ranges from $50,000-70,000 with senior business analysts earning an average salary in the range of $80,000-100,000. In San Francisco, the average range is from $60,000-80,000 with those with the most experience earning on average $90,000-100,000.
Data scientists in the United States can expect to earn an average salary of $90,000-140,000. The range is so large because of the many variables that impact and determine a salary in this field: geographic location, experience, job title, job responsibilities, and relevant skills training.
In New York City, the average annual salaries for data scientists typically fall in the range of $93,000-150,000. Data scientists in San Francisco can typically expect to earn an average salary in the range of $110,000-160,000.
We are living in a fast-paced, data-driven society where businesses and organizations are looking to capitalize on any advantage they can in order to get ahead. That means that the demand for business analysts and data scientists continues to grow. If you are someone who enjoys solving problems, has strong communication skills, and enjoys working with numbers and data, you might just find that one of these two careers is right for you.
Campbell, B. (2017, March 22). Data Science vs. Data Analytics - Why Does It Matter? Retrieved January 29, 2018, from https://dataconomy.com/2017/03/data-science-vs-data-analytics/
Granville, V. (2014, January 16). Data Scientist versus Business Analyst. Retrieved January 29, 2018, from https://www.datasciencecentral.com/profiles/blogs/data-scientist-versus-business-analyst
Ilangovan, R. (2017, November 28). What's the Difference Between Data Science and Business Analytics? Retrieved January 29, 2018, from https://hackernoon.com/whats-the-difference-between-data-science-and-business-analytics-117a2125e86b
Jain, K. (2014, September 9). Should I become a data scientist (or a business analyst)? Retrieved January 29, 2018, from https://www.analyticsvidhya.com/blog/2014/09/become-data-scientist-business-analyst/
Monnappa, A. (2017, December 13). Data Science vs. Big Data vs. Data Analytics. Retrieved January 29, 2018, from https://www.simplilearn.com/data-science-vs-big-data-vs-data-analytics-article
Pandey, A. (2016, November 24). Business Analytics Vs Data Analytics (Data Science). Retrieved January 29, 2018, from https://discuss.analyticsvidhya.com/t/business-analytics-vs-data-analytics-data-science/13486
Rajpurohit, A. (n.d.). Infographic - Data Scientist or Business Analyst? Knowing the Difference is Key. Retrieved January 29, 2018, from https://www.kdnuggets.com/2015/10/infographic-data-scientist-business-analyst-difference.html
Shartsis, A. (2017, May 18). What is the difference between a data scientist and a business intelligence analyst? Retrieved January 29, 2018, from https://www.quora.com/What-is-the-difference-between-a-data-scientist-and-a-business-inteligence-analyst