Both Data Science and Business Analytics add a lot of value to the companies, and the profit drawn is reaped by these big companies as well. This calls for hiring proficient developers and experts both for Data Science and Business Analytics roles.
We will take a look at the following concepts on this Data Science vs Business Analytics career path blog:
Let’s learn about the key differences between Data Science and Business Analytics now!
To gain a quick insight into the roles that are involved, corresponding to handling data, take a look at this:
Data Scientist: Responsible for solving data-related problems to bring a sense of usefulness to the company by converting a raw entity, such as data, and applying transformations onto it to eventually convert it into useful information.
Business Analyst: Responsible for handling the business decisions that take place in day-to-day activities. A Business Analyst acts as a bridge to actively gap the differences between the working of IT and the business side of operations.
In today’s competitive and enthusiastic world, there are a lot of people aspiring to build a career around these technologies. But to do so, it calls for immense research, clarity, and oversight about which career path would be the right one for you!
The Role of Data Science in IT Firms
In production environments and most IT firms, Data Scientists are a part of the frontend team who handle the process of data collection, perform organized analysis, and tie it all up later using numerous tools and techniques. You can enjoy a career in data science, the demand for an individual with these Data science skills keeps on increasing.
A Data Scientist will have the technical skills that are immeasurable when working with data collection and analysis.
Algorithm design to collect and analyze data to eventually help deploy these to various systems spanned across networks is a very vital skill.
Mathematics and concepts on Machine Learning and Deep Learning take the centerstage when one talks about becoming proficient in this field. The emphasis on these concepts is rightly put because the job demands a lot of trend seeking and the ability to perform exceptional predictive analytics.
A certification with a specialization in Data Science can help students or enthusiasts in developing the skills required for the industry and eventually help secure a good job.
Data Science Skills
Following are some of the skills and tools that a Data Scientist must have in his/her arsenal:
- Python
- Keras
- PyTorch
- Computer Vision
- Deep Learning
- Natural Language Processing
- Problem-solving
- Analytical Thinking
A Data Science role can span across a lot of dimensions, including a Research Scientist role or even a Senior Data Analyst role. Expert Data Analyst requires great knowledge of Data Science.
One thing is for certain, in today’s world, businesses are driven by data, and this adds nothing but immense value to the field and the confidence of learners.
Next up on this Data Science vs Business Analytics blog, is to know all about Business Analytics.
The Role of Buisness Analytics in IT Firms
Business Analytics revolves around the world of data extraction from structured and unstructured datasets.
Data governs certain decisions that are used to look back at past performances, analyze current standings, and forecast potential future performance.
A Business Analyst is involved in aiding business leaders by providing them with ample information and results from analytics to help drive the company towards success.
The important aspect of Business Analytics comes from a strong foundation in the concepts of statistical analysis and data management. Along with this, Business Analysts must also be adept in analytical planning and predictive analytics.
Business Analytics is a field that revolves around data visualization. It forms an integral part of this career path as it is one of the elegant ways to provide insights to the leaders based on the analysis.
Next up in this Business Analytics vs Data Science post, let us check the vital skills a Business Analyst must-have.
Business Analyst Skills
Following are a few of the technical and business skills that aspiring Business Analysts should consider having:
- Programming skills
- Statistical analysis
- Data querying tools
- Business Intelligence tools
- Data mining
- Analytical problem-solving
- Data visualization
As you might have already taken a guess, since data analysis is key to businesses across the globe, an ample number of job opportunities are being created every day.
Certification in Business Analytics will help prospects and learners secure roles such as Systems Analyst, Senior Business Analyst, Lead Data Analyst, and more.
The difference between Data Science and Business Analytics should be clear after you go through the following section.
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Career Paths for Data Scientists and Business Analysts
A Data Scientist’s primary assets are being involved in research, writing good code, and being proficient in Mathematics. This continues along the career path as well.
A Business Analyst, on the other hand, is involved with the development of strategies, building business-driven insights, and more.
One can compare the skills, and it is easy to notice that a Data Scientist’s role is more technical when directly juxtaposed with the role of a Business Analyst.
You must understand the fundamental differences that lie in Data Science and Business Analytics jobs.
The following is the order in which a Data Scientist and a Business Analyst can go about climbing the corporate ladder in the respective domains:
- Data Scientist
- Senior Data Scientist
- Chief Data Scientist
- Entrepreneur
Coming to a Business Analyst:
- Business Analyst
- Senior Business Analyst
- Analytics Expert
- Strategy Leader
Which is a better career option for you?
Before we move on to discuss which career path should be chosen, let us first look at some facts. As per Markets and Markets reports, the Data Science market is expected to grow to USD 140 Billion by 2024, and the Business Analytics market is expected to grow to USD 100 Billion. It is estimated that both the domains would grow further and prove to be a good career option. The only point that needs to be considered is which role do you find interesting and would love to do.
Both Data Scientist and Business Analyst roles are data-based roles but they differ a lot in terms of their usage in an organization. Data Science typically works on complex and very specific problems for the long-term growth of the company. Whereas, a Business Analyst is involved in both the analytics and business side of the organization. He drives data-driven business decisions and is responsible for communicating with IT and management simultaneously.
As a Business Analyst, you will be working with tools like Excel, Tableau, SQL, Python. Whereas, the commonly used tools by a Data Scientist are R, Python, Keras, scikit-learn, etc. The two roles may sometimes overlap based on the organization’s internal preferences, decisions, etc. Hence, knowing and understanding the exact day-to-day job in both roles is essential before deciding the career path.
Be it a Data Science role or a Business Analysis one, the number of job opportunities are virtually endless. The concepts are very elegant to learn and implement to solve a variety of problems. Be it Data Science and Business Analytics salary, the numbers have been nothing but impressive both in the USA and the rest of the world.
Conclusion
We hope the differences between Data Science and Business Analytics are clear to you now!
An important aspect to take away here is that each of these career paths has numerous advantages. Depending on what your inclination is and the factors mentioned above, you could go on and consider one of these top career paths to follow!