Название: Mastering Data Engineering and Analytics with Databricks: A Hands-on Guide to Build Scalable Pipelines Using Databricks, Delta Lake, and MLflow
Автор: Manoj Kumar
Издательство: Orange Education Pvt Ltd, AVA
Год: 2024
Страниц: 533
Язык: английский
Формат: epub (true)
Размер: 111.4 MB
Master Databricks to Transform Data into Strategic Insights for Tomorrow’s Business Challenges. In today’s data-driven world, mastering data engineering is crucial for driving innovation and delivering real business impact. Databricks is one of the most powerful platforms which unifies data, analytics and AI requirements of numerous organizations worldwide. Mastering Data Engineering and Analytics with Databricks goes beyond the basics, offering a hands-on, practical approach tailored for professionals eager to excel in the evolving landscape of data engineering and analytics. This book uniquely blends foundational knowledge with advanced applications, equipping readers with the expertise to build, optimize, and scale data pipelines that meet real-world business needs. With a focus on actionable learning, it delves into complex workflows, including real-time data processing, advanced optimization with Delta Lake, and seamless ML integration with MLflow—skills critical for today’s data professionals. Drawing from real-world case studies in FMCG and CPG industries, this book not only teaches you how to implement Databricks solutions but also provides strategic insights into tackling industry-specific challenges. From setting up your environment to deploying CI/CD pipelines, you'll gain a competitive edge by mastering techniques that are directly applicable to your organization’s data strategy. By the end, you’ll not just understand Databricks—you’ll command it, positioning yourself as a leader in the data engineering space. This book is designed for data engineering students, aspiring data engineers, experienced data professionals, cloud data architects, data scientists and analysts. A basic understanding of data engineering concepts, familiarity with data analytics, and some experience with cloud computing or programming languages such as Python or SQL will help readers fully benefit from the book’s content.
Название: Гены и геномы (в 2-х томах)
