Data science uses a multidisciplinary approach to discover patterns in data and deliver data-driven insights. Data scientists help build better products, services, and improve business metrics via advanced predictive analytics, visualizations, and machine learning.
Data analytics requires strong attention to detail, a focus on key metrics, and the willingness to communicate. While it is a universal skill, data/BI analysts usually work in specific business domains like digital marketing, risk management, retail analytics, etc.
For all the data requirements of organizations, the first thing they need to do is to establish a data architecture/platform and establish a pipeline to collect, transmit and transform data, which is what data engineering does.
DevOps is the backbone of modern agile software delivery and IT infrastructure. The outcomes of their work lead to more rapid application development and feature releases, scalability and resiliency of applications, greater automation across IT workflows, etc.