Difference between Business Analyst & Data Scientist

If there’s one thing that has emerged as a power to be calculated with in the world today its data. Data is driving and determining modern businesses exponentially. However, data in itself doesn’t hold much value for businesses unless it is examined and categorized.  Some experts who experiment 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 teamwork in a data driven setting, each of the roles includes different tasks and responsibilities. 

Data science and business analytics both are most popular career choices for young professionals right now. If the countless ways in which data work captivates you then you can choose from either of the two career paths after considering your educational background, skills and interests, experience. To help you select a career path, we have listed down the basics and requirements of each of these roles.

Difference between Data Science and Business Analytics

Data scientists are specialists responsible for analyzing, preparing, formatting, and maintaining information. It includes using skills pertaining to computer science, mathematics and statistics. Data scientists are also responsible for developing algorithms and sketch data implications. Since data science aims at opening complex data patterns by studying and understanding data sets, it is important that data scientists are well versed in multidisciplinary skill sets.

Read, more: Introduction of Data science

Business analysts, on the other side, are professionals who look into the ever changing needs of any business and contribute them in implementing those changes. Business analysis combines integrative skills like analytics, business shrewdness and domain knowledge. Business analysts are responsible for a range of tasks including understanding business requirements, laying out plans and developing criminal insights. They form a bridge of communication between diffrent departments in a business organization to execute any business plan.

Both these roles are in fact, similar in a lot of ways, since both involve data gathering, inference buildup and data modeling. The scope of data science and business analytics often overlaps and the skill sets are not mutually exclusive.

Job Description of Business Analyst

Let’s look into a sample business analyst job description to understand the numerous tasks and responsibilities involved in the role-

Overview of Business Analyst

We are looking for a business analyst for finance who will be responsible for leading projects, purifying processes and supporting systems used by the Finance and Accounting departments as business requirements change. The ideal candidate will work closely with business investors from teams within Finance and Accounting in all geographies to understand business challenges. He/she will drive process improvement different ideas with a focus on – scoping, coordinating, preparation, executing testing, and executing launch activities, and provide ongoing support.

Responsibilities in Business Analyst

• Involve with our existing and potential customers and help them to accept products and solutions to meet their business requirements
•  Ensure consistent development in product awareness, adoption, and usage by customers
• Showcase our product and solution concepts via presentations, demos, user evangelization and real documentation
• Lead detection meetings with IT and business users to understand the client’s business objectives and system/application needs.
• With an excellent understanding of product features and related latest technologies, design the solution.
•  Lead client training meetings
• Support clients and play a key role in promoting solution acceptance and practice.
• Provide regular and passable end-user response to the product team.

Requirements in Business Analyst

•  Any technical degree (Engineering, MCA) or business degree (MBA, BBA) from a reputed organization with a minimum of 4-5 years of experience in software or consulting industry
•  Must be able to manage multiple projects using strong planning and structural skills
•  Outstanding verbal, written and performance skills to prove solution concepts
• Strong relational skills with ability to effect and build effective customer relationships
•  Systems application skills: requirements/process analysis, theoretical and detailed design, configuration, testing, training, change management, and support
• Ability to set and manage customer prospects, and work self-sufficiently on project projects.
•  Must be able to travel, providing on-site referring work to clients when required and have the ability to work remotely from the office.

Job Description of Data Scientist

The following sample job description will help you understand the responsibilities handled by data scientists.

Overview of Data Scientist

We are looking for a highly skilled, experienced and fervent data-scientist who can come on-board and help create the next generation of data-powered tech product. The perfect candidate would be someone who has worked in a Data Science role before where in he/she is comfortable working with unknowns, assessing the data and the viability of applying scientific techniques to business problems and products, and have a track record of developing and organizing data-science models into live applications.

Job Responsibilities of Data Scientist

• Prove and drive deep technical skill in solving real world retail business problems through the app of machine learning
• Cooperate with other team members both within and outside the data science team to create and bring world class data science products
• Act as an SME on the floor and help shape data science capabilities
• Making monthly sprint plans, ordering requests from partner product teams
• Partnering with the product team to create key performance pointers and new practices for measurement
• Interpreting data into criminal insights for the investors
• Automate reporting for weekly business metrics, identify areas of chance to automate and scale ad-hoc examines.

Requirements of Data Scientist                             

• 3+ years of experience in analytics, data science, machine learning, artificial intelligence or comparable role Bachelor’s degree in Computer Science, Data Science/Data Analytics, Maths/Statistics or related discipline
• Experience in building and developing Machine Learning models in Manufacture systems
• Strong analytical skills: ability to make sense out of a variety of data and its relation to the business problem or chance at hand
• Strong programming languages skills: comfortable with Python – pandas, numpy, scipy, matplotlib; Databases – SQL and noSQL
• Strong communication skills: ability to both express/understand the business problem at hand as well as aptitude to discuss with non-data-science background stakeholders
• Comfortable dealing with vagueness and competing objectives.

       Also, read: What is the salary of data Scientist in India?

Data scientists and business analysts are expected to continually up skill and keep up-to-date of the newest technologies and developments in their own fields. Obviously, the choice cannot be an impulsive one. We are the best data science training institute in Bangalore, machine learning, artificial intelligence and python, block chain, deep learning training provider in Bangalore. If you want to learn any data science courses, Nearlearn is the best place to learn and you will get 100% placement support.