Description
Master Databricks to Transform Data into Strategic Insights for Tomorrow’s Business Challenges
Key Features
● Combines theory with practical steps to master Databricks, Delta Lake, and MLflow.
● Real-world examples from FMCG and CPG sectors demonstrate Databricks in action.
● Covers real-time data processing, ML integration, and CI/CD for scalable pipelines.
● Offers proven strategies to optimize workflows and avoid common pitfalls.
Book Description
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.
What you will learn
● Design and implement scalable, high-performance data pipelines using Databricks for various business use cases.
● Optimize query performance and efficiently manage cloud resources for cost-effective data processing.
● Seamlessly integrate machine learning models into your data engineering workflows for smarter automation.
● Build and deploy real-time data processing solutions for timely and actionable insights.
● Develop reliable and fault-tolerant Delta Lake architectures to support efficient data lakes at scale.
Who is this book for?
This book is designed for data engineering students, aspiring data engineers, experienced data professionals, cloud data architects, data scientists and analysts looking to expand their skill sets, as well as IT managers seeking to master data engineering and analytics with Databricks. 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.
Key Features
● Combines theory with practical steps to master Databricks, Delta Lake, and MLflow.
● Real-world examples from FMCG and CPG sectors demonstrate Databricks in action.
● Covers real-time data processing, ML integration, and CI/CD for scalable pipelines.
● Offers proven strategies to optimize workflows and avoid common pitfalls.
Book Description
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.
What you will learn
● Design and implement scalable, high-performance data pipelines using Databricks for various business use cases.
● Optimize query performance and efficiently manage cloud resources for cost-effective data processing.
● Seamlessly integrate machine learning models into your data engineering workflows for smarter automation.
● Build and deploy real-time data processing solutions for timely and actionable insights.
● Develop reliable and fault-tolerant Delta Lake architectures to support efficient data lakes at scale.
Who is this book for?
This book is designed for data engineering students, aspiring data engineers, experienced data professionals, cloud data architects, data scientists and analysts looking to expand their skill sets, as well as IT managers seeking to master data engineering and analytics with Databricks. 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.