Mastering Databricks Lakehouse Platform
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Mastering Databricks Lakehouse Platform
Enable data and AI workloads with absolute security and scalability KEY FEATURES ● Detailed, step-by-step instructions for every data professional starting a career with data engineering. ● Access to DevOps, Machine Learning, and Analytics wirthin a single unified platform. ● Includes design considerations and security best practices for efficient utilization of Databricks platform. DESCRIPTION Starting with the fundamentals of the databricks lakehouse platform, the book teaches readers on administering various data operations, including Machine Learning, DevOps, Data Warehousing, and BI on the single platform. The subsequent chapters discuss working around data pipelines utilizing the databricks lakehouse platform with data processing and audit quality framework. The book teaches to leverage the Databricks Lakehouse platform to develop delta live tables, streamline ETL/ELT operations, and administer data sharing and orchestration. The book explores how to schedule and manage jobs through the Databricks notebook UI and the Jobs API. The book discusses how to implement DevOps methods on the Databricks Lakehouse platform for data and AI workloads. The book helps readers prepare and process data and standardizes the entire ML lifecycle, right from experimentation to production. The book doesn't just stop here; instead, it teaches how to directly query data lake with your favourite BI tools like Power BI, Tableau, or Qlik. Some of the best industry practices on building data engineering solutions are also demonstrated towards the end of the book. WHAT YOU WILL LEARN ● Acquire capabilities to administer end-to-end Databricks Lakehouse Platform. ● Utilize Flow to deploy and monitor machine learning solutions. ● Gain practical experience with SQL Analytics and connect Tableau, Power BI, and Qlik. ● Configure clusters and automate CI/CD deployment. ● Learn how to use Airflow, Data Factory, Delta Live Tables, Databricks notebook UI, and the Jobs API. WHO THIS BOOK IS FOR This book is for every data professional, including data engineers, ETL developers, DB administrators, Data Scientists, SQL Developers, and BI specialists. You don't need any prior expertise with this platform because the book covers all the basics. TABLE OF CONTENTS 1. Getting started with Databricks Platform 2. Management of Databricks Platform 3. Spark, Databricks, and Building a Data Quality Framework 4. Data Sharing and Orchestration with Databricks 5. Simplified ETL with Delta Live Tables 6. SCD Type 2 Implementation with Delta Lake 7. Machine Learning Model Management with Databricks 8. Continuous Integration and Delivery with Databricks 9. Visualization with Databricks 10. Best Security and Compliance Practices of Databricks
Mastering Data Engineering and Analytics with Databricks
Author: Manoj Kumar
language: en
Publisher: Orange Education Pvt Ltd
Release Date: 2024-09-30
TAGLINE 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. 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 WILL YOU 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. TABLE OF CONTENTS SECTION 1 1. Introducing Data Engineering with Databricks 2. Setting Up a Databricks Environment for Data Engineering 3. Working with Databricks Utilities and Clusters SECTION 2 4. Extracting and Loading Data Using Databricks 5. Transforming Data with Databricks 6. Handling Streaming Data with Databricks 7. Creating Delta Live Tables 8. Data Partitioning and Shuffling 9. Performance Tuning and Best Practices 10. Workflow Management 11. Databricks SQL Warehouse 12. Data Storage and Unity Catalog 13. Monitoring Databricks Clusters and Jobs 14. Production Deployment Strategies 15. Maintaining Data Pipelines in Production 16. Managing Data Security and Governance 17. Real-World Data Engineering Use Cases with Databricks 18. AI and ML Essentials 19. Integrating Databricks with External Tools Index
Databricks Lakehouse Platform Cookbook
Author: Dr. Alan L. Dennis
language: en
Publisher: BPB Publications
Release Date: 2023-12-18
Analyze, Architect, and Innovate with Databricks Lakehouse KEY FEATURES ● Create a Lakehouse using Databricks, including ingestion from source to Bronze. ● Refinement of Bronze items to business-ready Silver items using incremental methods. ● Construct Gold items to service the needs of various business requirements. DESCRIPTION The Databricks Lakehouse is groundbreaking technology that simplifies data storage, processing, and analysis. This cookbook offers a clear and practical guide to building and optimizing your Lakehouse to make data-driven decisions and drive impactful results. This definitive guide walks you through the entire Lakehouse journey, from setting up your environment, and connecting to storage, to creating Delta tables, building data models, and ingesting and transforming data. We start off by discussing how to ingest data to Bronze, then refine it to produce Silver. Next, we discuss how to create Gold tables and various data modeling techniques often performed in the Gold layer. You will learn how to leverage Spark SQL and PySpark for efficient data manipulation, apply Delta Live Tables for real-time data processing, and implement Machine Learning and Data Science workflows with MLflow, Feature Store, and AutoML. The book also delves into advanced topics like graph analysis, data governance, and visualization, equipping you with the necessary knowledge to solve complex data challenges. By the end of this cookbook, you will be a confident Lakehouse expert, capable of designing, building, and managing robust data-driven solutions. WHAT YOU WILL LEARN ● Design and build a robust Databricks Lakehouse environment. ● Create and manage Delta tables with advanced transformations. ● Analyze and transform data using SQL and Python. ● Build and deploy machine learning models for actionable insights. ● Implement best practices for data governance and security. WHO THIS BOOK IS FOR This book is meant for Data Engineers, Data Analysts, Data Scientists, Business intelligence professionals, and Architects who want to go to the next level of Data Engineering using the Databricks platform to construct Lakehouses. TABLE OF CONTENTS 1. Introduction to Databricks Lakehouse 2. Setting Up a Databricks Workspace 3. Connecting to Storage 4. Creating Delta Tables 5. Data Profiling and Modeling in the Lakehouse 6. Extracting from Source and Loading to Bronze 7. Transforming to Create Silver 8. Transforming to Create Gold for Business Purposes 9. Machine Learning and Data Science 10. SQL Analysis 11. Graph Analysis 12. Visualizations 13. Governance 14. Operations 15. Tips, Tricks, Troubleshooting, and Best Practices