{ "item_title" : "Data Pipelines Pocket Reference", "item_author" : [" Dale D. Jarvis "], "item_description" : "BUILD, MANAGE, AND TROUBLESHOOT MODERN DATA PIPELINES WITH CONFIDENCEHow do raw datasets become reliable, usable information?How can data engineers design pipelines that are scalable, observable, secure, and resilient?What tools, architectures, and best practices should you understand when working with modern data systems?DATA PIPELINES POCKET REFERENCE is a practical resource for developers, data engineers, analysts, architects, and technology professionals who want a concise and useful reference for designing, building, operating, and troubleshooting modern data pipelines.Whether you're working with batch processing, streaming systems, cloud data platforms, APIs, databases, or distributed processing frameworks, this guide provides a structured overview of the concepts and practices that form the foundation of effective data engineering.WHAT YOU'LL FIND INSIDEData pipeline fundamentalsETL and ELT architecturesBatch and real-time processingData ingestion strategiesAPIs and database integrationFile-based data ingestionData transformation principlesData validation and quality checksData cleaning and normalizationWorkflow orchestrationScheduling and dependency managementPipeline monitoring and observabilityLogging and error handlingRetry strategies and failure recoveryData lineage and metadataData warehouses and data lakesLakehouse architectureDistributed data processingStreaming data conceptsEvent-driven architecturesMessage queues and event streamsPipeline security and access controlEncryption and sensitive data handlingScalability and performance optimizationCost optimizationTesting data pipelinesCI/CD for data engineeringInfrastructure and deployment considerationsTroubleshooting common pipeline failuresModern cloud data-engineering conceptsUNDERSTAND THE PIPELINE LIFECYCLEA reliable data pipeline involves much more than moving information from one location to another.Data must be collected, validated, transformed, transported, stored, monitored, and made available to downstream users and applications.This reference helps readers understand how these stages fit together and how architectural decisions affect reliability, performance, maintainability, and cost.FROM ETL TO MODERN DATA PLATFORMSTraditional ETL remains important, but modern organizations increasingly use combinations of ELT, cloud warehouses, data lakes, lakehouses, streaming platforms, orchestration systems, APIs, and distributed processing frameworks.Understanding the strengths and limitations of each approach can help data professionals choose appropriate solutions for different workloads.DESIGNED AS A PRACTICAL REFERENCEUse this book when learning data engineering fundamentals, reviewing concepts before an interview, planning a pipeline architecture, troubleshooting a workflow, or refreshing your knowledge of modern data infrastructure.The material is organized to make complex concepts easier to locate and review without requiring you to read an entire textbook from beginning to end.Understand the architecture. Build reliable pipelines. Engineer data with confidence.Get your copy of DATA PIPELINES POCKET REFERENCE and strengthen your foundation in modern data engineering.", "item_img_path" : "https://covers2.booksamillion.com/covers/bam/9/79/819/228/9798192287613_b.jpg", "price_data" : { "retail_price" : "86.99", "online_price" : "86.99", "our_price" : "86.99", "club_price" : "86.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }

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