{ "item_title" : "Analytics Engineer", "item_author" : [" Richard Boozman "], "item_description" : "Build trusted, scalable, and maintainable analytics systems for modern data organizationsRaw data is rarely useful on its own.Before organizations can make decisions, data must be cleaned, modeled, transformed, documented, tested, and structured into reliable analytical systems.That is the role of the modern analytics engineer.Analytics Engineer is a practical, engineering-focused guide to building production-grade analytics workflows using dbt, SQL modeling techniques, and modern data platform practices.This book teaches data professionals how to transform fragmented raw data into trustworthy business intelligence systems that scale across teams and organizations.Why analytics engineering mattersModern data teams face challenges such as: inconsistent business metricsduplicated transformation logicunreliable dashboards and reportingpoorly documented datasetsdifficult-to-maintain SQL pipelinesweak governance and testing practicesAnalytics engineering bridges the gap between data engineering and business intelligence by bringing software engineering discipline into analytics workflows.What you will learnfundamentals of analytics engineeringmodern ELT and transformation workflowsbuilding modular SQL models with dbtdimensional modeling and warehouse designtesting and validating analytical datadocumentation and lineage trackingreusable business metrics and semantic layersversion control and collaborative analytics workflowsorchestrating transformations in productionoptimizing query performance and warehouse costsFrom raw warehouse tables to trusted metricsThroughout the book, you will learn how to: structure maintainable transformation layersstandardize business definitions across teamsimprove reliability and trust in analytics systemsbuild scalable SQL modeling workflowsreduce technical debt in reporting pipelinesmanage analytics projects like production softwareEach chapter focuses on practical workflows used in modern analytics and data platform teams.Practical applicationsbusiness intelligence systemsanalytics transformation pipelinesKPI and reporting platformscustomer and product analyticsfinance and operations reporting systemsenterprise data warehouse workflowsThese examples reflect real-world analytical engineering challenges.Who this book is foranalytics engineersdata analysts transitioning into engineeringdata engineersBI developersSQL developersteams building modern data platformsIf you want to build analytics systems that are trusted, maintainable, and scalable, this book provides the roadmap.Model clearly.Transform reliably.Engineer analytics that teams can trust.", "item_img_path" : "https://covers2.booksamillion.com/covers/bam/9/79/818/030/9798180309761_b.jpg", "price_data" : { "retail_price" : "24.99", "online_price" : "24.99", "our_price" : "24.99", "club_price" : "24.99", "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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