{ "item_title" : "Fundamentals Of Data Engineering", "item_author" : [" Dale D. Jarvis "], "item_description" : "DATA ENGINEERING FUNDAMENTALSA Practical Guide to Data Pipelines, Architecture, Storage, Processing, Quality, Orchestration, and Modern Data PlatformsBUILD A STRONG FOUNDATION IN MODERN DATA ENGINEERINGHow does raw information become reliable, usable data?What does it take to build data systems that are scalable, maintainable, secure, and dependable?Which concepts should every aspiring data engineer understand before working with increasingly complex data platforms?DATA ENGINEERING FUNDAMENTALS provides a practical introduction to the core concepts, workflows, architectures, and engineering practices used to build modern data systems.From data ingestion and transformation to storage, orchestration, quality, security, and analytics, this guide brings the essential pieces together in one structured resource.WHAT YOU'LL EXPLOREFoundations of data engineeringThe modern data lifecycleData engineering roles and responsibilitiesData sources and data ingestionBatch and real-time data processingETL and ELT workflowsData transformation principlesData pipelines and workflow designRelational databasesNoSQL databasesData warehousesData lakesLakehouse architectureData modeling fundamentalsSchema design and evolutionData storage and file formatsDistributed data processingStreaming data conceptsWorkflow orchestration and schedulingData quality and validationData lineage and metadataMonitoring and observabilityPipeline testingError handling and recoveryData security and access managementPrivacy and sensitive-data considerationsCloud data platformsPerformance and scalabilityCost optimizationCI/CD for data systemsInfrastructure and deployment conceptsData architecture and engineering trade-offsUNDERSTAND THE DATA ENGINEERING LIFECYCLEData engineering is more than building pipelines.A successful data platform must reliably move information from source systems to destinations where it can be analyzed and used.That requires thoughtful decisions about ingestion, transformation, storage, processing, orchestration, quality, security, monitoring, and access.This guide connects those individual components so readers can understand how they work together as an engineering system.LEARN THE CORE ARCHITECTURAL CONCEPTSModern organizations may rely on operational databases, APIs, object storage, data warehouses, data lakes, streaming platforms, transformation tools, and orchestration systems.Understanding the purpose and limitations of these components helps data professionals select appropriate solutions instead of relying solely on technology-specific recipes.Understand the data lifecycle. Design reliable pipelines. Build better data systems.Get your copy of DATA ENGINEERING FUNDAMENTALS and develop a stronger foundation for modern data engineering.Important Disclaimer: This is an independently authored educational resource. It is not affiliated with, sponsored by, endorsed by, or officially connected with any author, publisher, cloud provider, software vendor, or certification organization. Technology platforms, tools, and best practices change over time; readers should consult current official documentation when implementing production systems.", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/9/79/819/229/9798192295212_b.jpg", "price_data" : { "retail_price" : "76.99", "online_price" : "76.99", "our_price" : "76.99", "club_price" : "76.99", "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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