Paperback. Business intelligence is no longer just about building dashboards.Modern organizations expect data to be accurate, available when it is needed, scalable as the business grows, and trustworthy enough to support financial, operational, and strategic decisions. Behind every reliable dashboard is an engineering system-and building that system requires much more than knowing SQL or a BI tool.Modern BI Engineering is a practical guide to designing, building, and operating the data infrastructure that turns raw business data into reliable, actionable intelligence.Instead of focusing on isolated tools or simplistic tutorials, this book takes you through the complete BI engineering lifecycle: from source systems and data ingestion to transformation, data modeling, warehousing, orchestration, semantic layers, dashboards, governance, security, and production operations.You will learn how the different pieces fit together-and, more importantly, why the decisions made at one stage can affect everything downstream.Inside the Book, You Will Learn How To: Understand the evolution of modern business intelligence and the architecture behind today's data platformsDesign reliable ETL and ELT pipelines for real-world data environmentsWork with relational databases, APIs, files, application data, and external data sourcesChoose between batch, incremental, and real-time ingestion strategiesClean, standardize, validate, and transform messy business dataHandle missing values, duplicates, outliers, inconsistent records, and changing source schemasDesign dimensional models and star schemas using fact and dimension tablesImplement and reason about slowly changing dimensionsOrchestrate complex pipelines with dependencies, scheduling, retries, backfills, and automationMonitor pipelines through logging, observability, and operational reliability practicesDesign semantic layers that keep business metrics consistent across reports and dashboardsBuild effective dashboards, reports, KPIs, and self-service analytics environmentsUnderstand the role of cloud data warehouses, data lakes, lakehouses, and medallion architectureExplore distributed processing, streaming, and near-real-time analyticsApply data security, access control, privacy, governance, metadata, lineage, and responsible analytics practicesIntroduce testing, version control, CI/CD, deployment, performance optimization, scalability, and cost management into BI systemsThink beyond individual pipelines and design complete enterprise BI platformsFollow an end-to-end journey from raw data to an executive dashboardThis book focuses on that reality.You will encounter the engineering problems that often get ignored in introductory BI material: what happens when a pipeline runs twice, when data arrives late, when an upstream system changes unexpectedly, when historical records need to remain accurate, or when two departments calculate the same business metric differently.The goal is not simply to show you how something works, but to help you understand why it works, what can go wrong, and how to design systems that can be trusted.It is particularly suited for: Data engineersBI developersAnalytics engineersData analystsSoftware engineersSelf-taught data professionalsExperienced engineersAdvanced students and technical professionalsYou do not need to master every technology mentioned in the book. The emphasis is on the engineering principles, architectural patterns, Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

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Detalles bibliogr�ficos

T�tulo: Modern BI Engineering (Paperback)
Editor: Independently Published
Fecha de publicaci�n: 2026
Idioma: Ingl�s
ISBN 13: 9798172069598
Encuadernaci�n: Paperback
Estado: new

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Sinopsis

Business intelligence is no longer just about building dashboards.

Modern organizations expect data to be accurate, available when it is needed, scalable as the business grows, and trustworthy enough to support financial, operational, and strategic decisions. Behind every reliable dashboard is an engineering system—and building that system requires much more than knowing SQL or a BI tool.

Modern BI Engineering is a practical guide to designing, building, and operating the data infrastructure that turns raw business data into reliable, actionable intelligence.

Instead of focusing on isolated tools or simplistic tutorials, this book takes you through the complete BI engineering lifecycle: from source systems and data ingestion to transformation, data modeling, warehousing, orchestration, semantic layers, dashboards, governance, security, and production operations.

You will learn how the different pieces fit together—and, more importantly, why the decisions made at one stage can affect everything downstream.

Inside the Book, You Will Learn How To:

Understand the evolution of modern business intelligence and the architecture behind today's data platforms
Design reliable ETL and ELT pipelines for real-world data environments
Work with relational databases, APIs, files, application data, and external data sources
Choose between batch, incremental, and real-time ingestion strategies
Clean, standardize, validate, and transform messy business data
Handle missing values, duplicates, outliers, inconsistent records, and changing source schemas
Design dimensional models and star schemas using fact and dimension tables
Implement and reason about slowly changing dimensions
Orchestrate complex pipelines with dependencies, scheduling, retries, backfills, and automation
Monitor pipelines through logging, observability, and operational reliability practices
Design semantic layers that keep business metrics consistent across reports and dashboards
Build effective dashboards, reports, KPIs, and self-service analytics environments
Understand the role of cloud data warehouses, data lakes, lakehouses, and medallion architecture
Explore distributed processing, streaming, and near-real-time analytics
Apply data security, access control, privacy, governance, metadata, lineage, and responsible analytics practices
Introduce testing, version control, CI/CD, deployment, performance optimization, scalability, and cost management into BI systems
Think beyond individual pipelines and design complete enterprise BI platforms
Follow an end-to-end journey from raw data to an executive dashboard

This book focuses on that reality.

You will encounter the engineering problems that often get ignored in introductory BI material: what happens when a pipeline runs twice, when data arrives late, when an upstream system changes unexpectedly, when historical records need to remain accurate, or when two departments calculate the same business metric differently.

The goal is not simply to show you how something works, but to help you understand why it works, what can go wrong, and how to design systems that can be trusted.

It is particularly suited for:

Data engineers
BI developers
Analytics engineers
Data analysts
Software engineers
Self-taught data professionals
Experienced engineers
Advanced students and technical professionals

You do not need to master every technology mentioned in the book. The emphasis is on the engineering principles, architectural patterns, trade-offs, and reasoning that remain useful even as individual tools and platforms evolve.

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