Microsoft Excel Business Intelligence Handbook : Power Query, Power Pivot, Data Modeling, DAX, and Power BI for Enterprise Analytics
Language: English
Published by Independently Published Okt 2026, 2026
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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£ 31.66
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- Title
- Microsoft Excel Business Intelligence Handbook : Power Query, Power Pivot, Data Modeling, DAX, and Power BI for Enterprise Analytics
- Author
- Kai Ellington
- Publisher
- Independently Published Okt 2026
- Publication year
- 2026
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 13
- 9798160992686
- Item weight
- 929 grams
- Dimensions
- 279x216x21 mm
- Series
- Book 2 of 4: AI-Driven Reporting and Presentations with Microsoft Copilot: Practical Power BI and PowerPoint Workflows for Clear Insights
Microsoft Excel Business Intelligence Handbook
Power Query, Power Pivot, Data Modeling, DAX, and Power BI for Enterprise Analytics
Excel becomes significantly more powerful when it is treated not simply as a spreadsheet, but as part of a structured business intelligence system.
Microsoft Excel Business Intelligence Handbook provides a practical, architecture-focused guide to building reliable analytical solutions with Excel, Power Query, Power Pivot, the Excel Data Model, DAX, PivotTables, dashboards, and Power BI. Rather than focusing only on individual features or formulas, this book explains how these capabilities work together across the complete analytics lifecycle—from source data to validated business insight.
You will learn how to design repeatable Power Query pipelines, clean and combine data from multiple sources, build relational and dimensional models, establish appropriate relationships, and structure analytical models around business processes rather than report layouts. The book then moves into DAX, explaining measures, filter context, row context, CALCULATE, iterators, virtual tables, ranking, segmentation, variance analysis, and time intelligence through practical analytical patterns.
The book also examines the layer that often determines whether an Excel solution remains useful over time: the semantic and operational architecture. You will learn how to define metrics and KPIs consistently, build reusable measures, design analytical PivotTables and dashboards, manage refresh processes, improve performance, validate results, document models, and establish practical governance.
Topics include:
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Power Query for repeatable data acquisition and transformation
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Data cleaning, validation, quality engineering, and exception handling
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Combining Excel files, databases, CRM exports, and other business sources
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Power Pivot and the Excel Data Model
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Fact tables, dimension tables, relationships, and star schemas
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DAX measures, calculated columns, and evaluation context
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CALCULATE, FILTER, iterators, virtual tables, and advanced analytical patterns
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Time intelligence, period comparisons, rolling analysis, and trend evaluation
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Business metrics, KPIs, targets, variances, and semantic definitions
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PivotTables, PivotCharts, slicers, timelines, and analytical dashboards
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Refresh architecture, performance optimization, documentation, and governance
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Designing production-grade Excel BI solutions
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Understanding where Excel fits within the broader Power BI and Microsoft data ecosystem
Throughout the book, the emphasis is on business meaning, data structure, analytical correctness, repeatability, and maintainability. Examples are designed to help you understand not only what to build, but why a particular architecture or calculation pattern is appropriate.
Whether you are an Excel power user moving toward business intelligence, a business or financial analyst building recurring reports, a data professional working with Microsoft technologies, or a BI practitioner looking to strengthen your Excel-based analytical workflows, this book provides a structured foundation for designing solutions that can grow beyond the traditional spreadsheet.
The central idea is simple: good business intelligence does not begin with a dashboard. It begins with a well-defined question, trustworthy data, a sound model, and clearly defined analytical logic.
This book shows you how to build that foundation in Excel.
"Synopsis" may belong to another edition of this title.
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