Business Analytics and Data Science – these two terms are co-related and undisputedly both these sectors are undergoing skyrocketing growth. At present, Business analytics holds a market size of around $70 Billion and Data Science $40 billion. The market size by 2025 is expected to reach by $100 Billion and $140 billion respectively. This means we can expect an upsurge in demand for these two flourishing profiles. Of these, Data science is the hottest career field in the market and quickly gaining popularity over business analytics.
There are millions of aspirants and analytic professionals who want to choose between ‘Business Analytics’ or ‘Data Science’ as their career; but they’re not sure about the prospects & distinction between these two roles. Before we dive into your choice, you should be clear about which path you wish to take, right? After all, it can turn into a career-defining point.
Here’s what we will suggest - follow our blog and you will get complete clarity between these two roles and introduce a methodology to decide which is the best - business or data science learning path based on factors like education, skills, and others.
Difference Between Data Analyst And Business Analyst: Simple Analogy
Let’s take an example of an electronics start-up. It will create job families such as: Scientists, Engineers, and Management professionals. Now we will take time and see what kind of role they will play in the firm.
We can decide their role from a basic understanding level:
Data Science And Business Analytics Job Role: Technical
This is a very basic term that you need to keep in mind while differentiating the role from Data Analyst To Data Scientist and Business Analysts.
Although these terms are commonly used in the industry, the exact role could depend on the experience of your company in data initiatives. Now that we have our basic terminology clear, let us see the kinds of problems solved by various Data scientists and Business Analysts.
Data Scientist And Business Analyst: Solutions
To understand the difference between a business analyst and data scientist, you should know the problems or projects they are working on. Let us take an example – Imagine you’re a C. A and you decide to implement two important projects. You have a team of data scientists & business analysts. How will you define the job? Here are two problem statements:
Take your time to understand the problems and figure out which problem is the best suited for your profile. In the first problem, you will have to make several business assumptions & incorporate macro changes in the strategy. This will require more business expertise & decision-making. It will be the job of a business analyst.
The second problem, it requires processing vast behavourial data from customers and understanding their hidden patterns. For this, an individual should have a good understanding of problem formulation & algorithms. A data scientist would be the ideal person to tackle this kind of specific & complex problem.
Data Science And Business Analytics: Skills & Tools
Data Scientist has to be proficient in Linear Algebra, Programming like C++, Java, and Python, and computer science fundamentals. Some instances include varying from building recommendations to personalized messages.
The common tools used by Data Scientists include R, Python, Keras, Numpy, Pandas, PyToch. And the commonly used techniques are Statistics, Machine Learning, Deep Learning, and NLP. On the other hand, Business Analytics should be proficient in presenting business simulations & business planning. A major part of their job role will be to analyze business trends and techniques. For instance, web analytics or pricing analytics. Some tools extensively used by business analysts are Excel, Tableau, SQL, and Python. And the most common techniques will be – Statistical Methods, Forecasting, Predictive Modelling, and storytelling.
Well, we can see the key differences in both the roles, but structure thinking & problem foundation are the key skills to perform well in your respective domains.
Data Science And Business Analytics Roadmap: Career Path
A Data Scientist's strengths lie in coding, maths, and research abilities. He or she requires continuous learning through the career journey.
A business Analyst needs to be more of a strategic thinker & should have a strong ability in project management. He or she tends to take business, strategic, and entrepreneurship roles as they progress through their career. While Data scientists adapt more to tech-entrepreneur roles because they are sound in technical background.
Refer to the following career path to see a more in-depth route from the start of Data Science & Business Analytics Journey:
On An Ending Note –
Over here we have covered basic points about the key difference between Data Science and Business Analytics. If you wish to learn in-depth about these two crucial business elements, you can take up the course and build a strong foundation.
There are a lot of business analytics courses in the market that will answer curious questions like: What is Business Analytics? What Is Data Science? A career in Business Analytics Or Data Science, Spectrum Of Business Analytics, MIS, BI, Predictive Modelling, AI & ML, Skills Required in Business Analytics Roles, Data Science Roles, etc.
However, if you’ve set your heart on a data science role, check out Ekeeda's ultimate Data Science Online Course designed for students and young professionals. What’s more? Get industry-relevant training, 1:1 live classes, 100+ assignments and capstones, and placement assistance in top techs and start-ups such as Datascope, Tiger Analytics, Cloudera, Brainvire, IBM, Yalantis, Peerbits, and more.
Set a clear Data Science Roadmap which defines the milestones in your career journey. Use this roadmap to track your Data Science Journey, see where you stand in preparation and what is your next move!
Our users have achieved so much in just a little time.
Data science in logistics industry – Know the growing importance of data science for logistics, shipping, current trends, and tools for the data science logistics industry. Click to know more!
Know the key roles of data science in today’s business world, what the future looks like, data science transform, and more. Explore the role of data scientists. Click now!
Know about what the future holds for data science, tech advances, sectors reliable on data science & best data science career opportunities for you. Click now!
Deep Learning In Data Science – What is Deep Learning, learn data science, use of deep learning in data science, its impact and benefits. Click to find out more!
Role of Data Science – Learn how data science play important role in our lives – entertainment, digital ads, logistics, e-commerce, games. Click to know more!
Data Science In Agriculture Sector – Importance of data science and its use in agriculture sector, challenges, real-life data science instances in farming, etc. Click now!
Data Science In Gaming Industry – What do data scientists do in gaming industry – data collection, fraud detection, personalized ads, gaming curiosity, etc. Click now!
Know six steps to create a smart app using data science - Personalize Experience, Real Time Monitoring, Embrace Data Science, ML, Model Operations, etc. Visit online!
Work-life Balance is important in everyday life. Know how to maintain it whilst your career in data science. Get tips and tricks from fortune 500+ DS experts. Read more!
Looking for a data science career? Here are 6 compelling reasons why it’s a dream career – company demands, massive data floating, versatile field, prestigious, excellent pay, etc.
Join our army of 50K subscribers and stay updated on the ongoing trends in the design industry.
Your test is submitted successfully. Our team will verify you test and update in email for result.