Difference between Data Scientist and Business Analyst
DATA SCIENTIST |
BUSINESS ANALYST |
A data scientist analyzes, formats and extract data to predict insights from data . | A business analyst analyzes client and business requirement. |
Generally a data scientist analyzes patterns in the data and make suitable decisions. | Generally a business analyst interacts with clients and project managers to analyze their needs. |
Mostly they work only with structured data. | Where as a business analyst works with both structured and unstructured data. |
They perform predictive and prescriptive analysis. | They perform retrospective and descriptive analysis. |
They need to know Python, R, SAS, Spark, Tensorflow, Hadoop etc. | They need to know SQL, R, Tableau, and Excel etc. |
They uses tools like data warehousing, data visualization and machine learning etc. | They uses tools like Axure, Blueprint, Bit impulse etc. |
Annual average salary of a data scientist is about $120K. | Annual average salary of business analyst is about $70K. |
They use models like schema on query. | They use models like schema on load. |
Data scientists work on e-commerce, social media, finance, banking, IoT application industries. | Where as business analysts work is limited to businesses and consultancy services. |
Difference between Data Scientist and Business Analyst
In today’s world where data is all around everyone relies on data professionals who can analyze and extract data to predict insights from the big data. Data Scientists and Business Analysts are the two main data professionals who deal with data to make informed decisions for organizations. They both handle data to predict insights, and their skills, approaches, and objectives may differ significantly.
In this article, we will explore the main difference between Data Scientists and Business analysts, the skills required, and the responsibilities of both roles.