Data engineering (Big Data,Machine Learning,Deep Learning)

Abstract

Data engineering is a field of data science that focuses on designing, building, and maintaining the data infrastructure that supports data-driven organizations. This infrastructure includes data pipelines, databases, data warehouses, and data lakes, among others. Data engineering is a critical function in any data-driven organization because it enables data scientists, analysts, and other stakeholders to access, transform, and analyze data to derive insights and make informed decisions. In this article, we will explore what data engineering is, why it is important, the skills required to be a data engineer, and the tools and technologies used in data engineering. We will explore some of the key concepts and technologies involved in data engineering, including big data, machine learning, and deep learning.