Difference Between Data-Scientist, Data-Analyst And Business-Analyst
Data Analysts and Business Analysts both assist in data-driven decision-making in their organizations. Data Analysts tend to work more closely with the data itself, while Business Analysts tend to be more involved in addressing business needs and recommending solutions.
In today’s blog, we’ll investigate what makes every job special and why you could decide to pursue either as a profession.
Technology advancements and ubiquitous computing are spawning massive amounts of data, and we are now learning to utilize it to pursue better decisions. Therefore, we are seeing a significant rise of mathematicians, PC researchers, and analysts in different enterprises attempting to make sense of all this data using analytics tools and strategies. There is no branch of business, science, and engineering left untouched by Data Analytics.
- Under 0.5% of all information is investigated and utilized.
- 5% of all data is analyzed and used
- By 2025, the data science analytics sector in India alone is estimated to develop by 7x to reach $16 billion
- Right now, the US drives the data science job market encouraging a demand for 200,000 data scientists in the upcoming years.
- 1.8 MB of new data is created every 1 second—by each person in the world.
- Approximately, 70,000 search queries are performed on Google, and 1.2 trillion searches are done each year.
How to Choose Among a Career as a Data Analyst, Business Analyst and Data Scientist ?
Business Analysts and Data Analysts have comparatively similar job roles, and a few companies might use the terms interchangeably. However, keeping in mind that the two kinds of Analysts use data to improve business decisions, they do so in various ways.
What actually does Data Analysts do?
Data Analysts gather, clean, examine, visualize, and present existing data to help inform business decisions. An effective Data Analyst transforms data to answer a question and empower decision makers to plot the best course of action. General tasks performed by a Data Analyst includes:
- Working with business leaders and stakeholders to define a problem or business need
- Recognizing and obtaining information
- Cleaning and preparing data for analysis
- Analyzing data for patterns and trends
- Envisioning data to make it easier to understand
- Presenting data in such a way that it tells a compelling story
What do Business Analysts do?
Business Analysts help identify problems, opportunities, and solutions for their organizations. They do this by:
- Evaluating their organization’s current functions and IT structures
- Reviewing processes and interviewing team members to identify areas for improvement
- Presenting findings and recommendations to management and other key stakeholders
- Creating visuals and financial models to support business decisions
- Training and coaching staff in new systems.
These Experts are somewhat of a hybrid between business and data analysts. They use analysis, modeling, and visualization of industry trends and the competitive landscape to help businesses cut losses and increase profits.
What do Data Scientists do?
The following sample job description will help you understand the responsibilities handled by data scientists.
Job Responsibilities of Data Scientist
- Demonstrate and drive deep technical expertise in solving real world retail business problems through the application of machine learning
- Collaborate with other team members both within and outside the data science team to create and deliver world class data science products
- Act as an SME on the floor and help build data science capabilities
- Preparing monthly sprint plans, prioritizing requests from partner product teams
- Partnering with the product team to create key performance indicators and new methodologies for measurement
- Translating data into actionable insights for the stakeholders
- Automate reporting for weekly business metrics, identify areas of opportunity to automate and scale ad-hoc analyses
Job Requirements of Data Scientist
- Data science, machine learning or comparable role Bachelor’s degree in Computer Science, Data
Science/Data Analytics, Math/Statistics or related discipline
- Experience in building and deploying Machine Learning models in Production systems
- Strong analytical skills: ability to make sense out of a variety of data and its relation/applicability to the business problem or opportunity at hand
- Strong programming skills: comfortable with Python – pandas, numpy, scipy, matplotlib; Databases – SQL and noSQL
- Strong communication skills: ability to both formulate/understand the business problem at hand as well as ability to discuss with non data-science background stakeholders
- Comfortable dealing with ambiguity and competing objective
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Business and Data Analysts can emerge out of a wide variety of academic backgrounds, though most organizations search for candidates with at least a bachelor’s degree.
In common scenarios, business analysts might have a degree in a business-related field, while data analysts often have degrees in STEM fields like statistics, math, or computer science.
Earning a graduate degree with a focus on Data Analytics could help open opportunities for advancement in either field.
Skills: Business vs. Data Analyst vs. Data-Scientist
The difference between Business Analysts and Data Analysts is primarily based on how each of them deal with data. There are, in fact, quite a lot of similarities between these two roles, and depending on the company size, these roles can be interchangeable.
Business analysts deal with business implications of data and how to use them in any business environment to achieve the desired results. Data analysts, on the other hand, primarily analyze data to identify and reveal patterns, draw conclusions and insights from random data. In a way, one could say that the reports created by data analysts help business analysts in supporting their business decisions.
Even from a skillset point of view, there are differences between business analysts and data analysts. Data analysts need to know data science, data mining, data modeling, basic statistics, and maybe even big data analytics. Business analysts, on the other hand, need to know how to grow any business, apart from knowing the data skills.
Data scientists and business analysts are expected to constantly upskill and keep abreast of the latest technologies and developments in their respective fields. Clearly, the decision cannot be an impulsive one. Refer to the curriculum of data science and business analysis for further details so that you are certain of the path you choose.
The good news is that all these roles let you capitalize on your love for data. Data analysts are all about analyzing data sets and uncovering the trends to use in making an informed decision in organizations.
On the other hand, business analyst professionals are critical thinkers, problem solvers, and excellent communicators. These professionals have a detailed knowledge of their organization’s objectives and processes so they can evaluate performance, identify inadequacies, and advise and implement solutions.
If your question is, can a data analyst become a business analyst? Well, a data analyst can, over time, switch to the role of a business analyst. The same is true in reverse.
Difference between Business Analyst, Data Scientist and Data Analyst
Business analysts work only with structured data.
Business analysts need to know SQL, R/Python, Tableau, and Excel.
Business analysts look into client and business requirement.
Data Scientists work with both structured and unstructured data.
Data Scientists need to know Python/ R, SAS, ML, Deep Learning etc.
Data scientists primarily analyze data, create model, and develop dataset processes for production environment.
Business analysts need to know how to use data for business ends.
Business Analyst responsibilities include data entry, complex calculations, extrapolation and interpretation, troubleshooting, and more.
Business analysts generally have a background in statistics and data science.
Business Analysts are professionals who look into the ever changing needs of any business and assist them in implementing those changes. They form a bridge of communication between various departments in a business organization to execute any business plan.
Wherein, Data Scientists are responsible for developing algorithms and drawing data inferences. Since Data Science aims at unveiling complex data patterns by studying and understanding data sets, it is important that data scientists are well versed in multidisciplinary skill sets.
Both these roles are in fact, similar in a lot of ways, since both involve data gathering, inference accumulation and data modeling. The scope of data science and business analytics often overlap and the skill sets are not mutually exclusive. In any business environment, data scientists and business analysts work closely to understand and implement strategies.
Typically, data science can be taken up by early career professionals but business analytics is better suited for professionals with experience in business development, technology and project management..
Experts who dabble in data analytics can either be from a data science or a business analytics background. While both data scientists and business analysts are often seen working in close collaboration in a data driven environment, each of the roles involves different tasks and responsibilities.
Both data science and business analytics are popular career choices for young professionals today. If the myriad ways in which data work fascinates you then you can choose from either of the two career paths after considering your educational background, experience, skills and interests. To help you choose a career path, we have listed down the essentials and requirements of each of these roles.
Let us now look at the salary difference in roles of a data analyst and a business analyst.
The in-demand skills involved in data and business analysis often draw high salaries. According to Glassdoor, Business Analysts in the US in the year 2021 earn an average base pay of $77,218, while Data Analysts bring in an average base pay of $69,517 [1, 2].
Business Analysts are responsible for a range of tasks including understanding business requirements, laying out plans and developing actionable insights. Data Scientists, on the other hand, are professionals responsible for Analyzing, Preparing, formatting, and maintaining information. Business analysis combines integrative skills like analytics, business acumen and domain knowledge, whereas data science involves skills pertaining to computer science, mathematics and statistics.
Data Scientist Salary
Data scientist salaries in India start from ₹500,000 per annum and go upto more than ₹ 2,000,000 per annum, depending on the number of years of experience and skill set of the data science professional.
Freshers with 0 to 5 years of experience can expect to earn around ₹600,000-12,00,000 per annum.
Mid-level data scientists with 5 to 10 years of experience can expect to earn close to ₹25,00,000 per annum while senior data scientists with more than 10-12 years of experience can expect anything around greater than ₹30,00,000 per annum.
Business Analyst Salary
The average salary of a business analyst in India is around ₹700,000 per annum. As with any other domain, business analysts’ salaries depend on the years of experience and the extent of the expertise.
An Entry level business analyst with 1 to 2 years experience can expect to earn anything around ₹ 600,000 per annum while a mid-level analyst can earn anything from ₹12,00,000-26,00,000 per annum. Senior business analysts with 10 or more years of experience can earn anything around ₹25,00,000-40,00,000 per annum.
With both data scientists and business analysts, the recruiting company also makes a difference. Companies like Accenture, Cognizant, Mu Sigma, JP Morgan seem to be the top companies to work with.
Data Analyst Salary
As per Glassdoor The national average salary for a Fresher Data Analyst is ₹5,80,000 in India.
Tata Consultancy Services – ₹4,80,000/yr
Accenture – ₹5,86,964/yr
Cognizant Technology Solutions – ₹5,22,629/yr
Amazon – ₹5,38,244/yr
Capgemini – ₹4,14,034/yr
Infosys – ₹5,36,622/yr
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