
BOOKS - Ultimate Data Engineering with Databricks Develop Scalable Data Pipelines Usi...

Ultimate Data Engineering with Databricks Develop Scalable Data Pipelines Using Data Engineering's Core Tenets Such as Delta Tables, Ingestion, Transformation, Security, and Scalability
Author: Mayank Malhotra
Year: 2024
Pages: 243
Format: PDF | EPUB
File size: 10.1 MB
Language: ENG

Year: 2024
Pages: 243
Format: PDF | EPUB
File size: 10.1 MB
Language: ENG

Long Description of the Plot: In the book "Ultimate Data Engineering with Databricks," we embark on a journey to explore the core tenets of data engineering and their application in developing scalable data pipelines using Databricks. As we delve into the world of data engineering, we discover the importance of delta tables, ingestion, transformation, security, and scalability in creating efficient and reliable data pipelines. The book provides a comprehensive understanding of these concepts and their practical applications, equipping readers with the skills necessary to develop and maintain successful data engineering projects. The story begins with an introduction to data engineering and its significance in today's technology landscape. We learn how data engineering has evolved over time, from its humble beginnings to its current state-of-the-art practices. We understand the need for a personal paradigm for perceiving the technological process of developing modern knowledge, and how it can be the basis for the survival of humanity and the unification of people in a warring state. This sets the stage for our exploration of the core tenets of data engineering and their role in shaping the future of data pipelines. Delta Tables Ingestion: The Heart of Scalable Data Pipelines We begin by examining the concept of delta tables ingestion, which is at the heart of scalable data pipelines. Delta tables ingestion involves the process of capturing changes made to data in a table and applying those changes to create a new version of the table that reflects the latest state of the data.
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