Fundamentals of Data Engineering Building Robust Data Systems for Modern Analytics and Insights
Fundamentals of Data Engineering Building Robust Data Systems for Modern Analytics and Insights by Daniel Garfield
English | 2023 | ISBN: B0CFJR11JD | 105 pages | EPUB | 0.64 Mb
English | 2023 | ISBN: B0CFJR11JD | 105 pages | EPUB | 0.64 Mb
Introduction to Data Engineering
A. The role and importance of data engineering in the modern data landscape
In the ever-evolving world of technology, data has become the lifeblood of organizations across industries. From e-commerce giants to healthcare providers, companies are harnessing the power of data to drive decision-making, optimize operations, and gain a competitive edge. However, the increasing volume, velocity, and variety of data pose significant challenges when it comes to storage, processing, and analysis. This is where data engineering steps in as a crucial component of the modern data landscape.
Data engineering encompasses the set of practices and tools used to design, build, and manage the infrastructure required for data storage, processing, and integration. It involves the development of robust data pipelines that enable the smooth flow of information from various sources to the end users, such as data scientists, analysts, and business stakeholders. Data engineers are the unsung heroes behind the scenes, responsible for creating and maintaining the foundation upon which data-driven insights are built.