Mastering Data Engineering And Analytics With Databricks, A Hands-on Guide To Build Scalable Pipelines Using Databricks, Delta Lake, And MLflow

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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. Table of Contents SECTION 1

Introducing Data Engineering with Databricks
Setting Up a Databricks Environment for Data Engineering
Working with Databricks Utilities and Clusters

SECTION 2

Extracting and Loading Data Using Databricks
Transforming Data with Databricks
Handling Streaming Data with Databricks
Creating Delta Live Tables
Data Partitioning and Shuffling
Performance Tuning and Best Practices
Workflow Management
Databricks SQL Warehouse
Data Storage and Unity Catalog
Monitoring Databricks Clusters and Jobs
Production Deployment Strategies
Maintaining Data Pipelines in Production
Managing Data Security and Governance
Real-World Data Engineering Use Cases with Databricks
AI and ML Essentials
Integrating Databricks with External Tools

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Mastering Data Engineering And Analytics With Databricks, A Hands-on Guide To Build Scalable Pipelines Using Databricks, Delta Lake, And MLflow

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