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Microsoft Power BI For Dummies, 2nd (Jack A. Hyman)(Z-Library)

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Big Data
Language English

Make smarter business decisions with Microsoft PowerBI Microsoft PowerBI For Dummies gives you the foundation you need to use this powerful software platform to manage your data and gather insight for making better decisions. With PowerBI, you can visualize, model, and interpret large datasets, quickly revealing insights that once took weeks to dig out. This book takes you through the basics of getting your data ready, preparing your analysis, and creating reports. Then, you'll dig into more advanced features using DAX—the PowerBI programming language—even if you have no prior programming experience. This edition covers the latest updates to the software, including AI integration, enhanced customization, and improved real-time collaboration tools. Transform raw data into meaningful information and make data-driven decisions Import datasets and create dashboards, visualizations, and reports Use the Copilot AI assistant to speed up workflows...

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Whole-book reading guide from stratified index samples; jump to passages in the text

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【One-Line Pitch】 A practical, role-aware tour of Microsoft Power BI that takes you from raw data to governed, shareable dashboards—now with Copilot AI, Fabric, and real-time collaboration. Best for business analysts, Excel power users, and IT professionals who need a working foundation rather than a technical deep-dive. 【Book Arc】 - **Opening (~0%–12%)**: Frames data analytics in Power BI terms—what data is, how Power BI works under the hood, and the vocabulary you need before touching the tool. Solves the "I don't know what I don't know" problem. - **Early (~12%–27%)**: Moves into product choices and setup: Power BI versus Excel, the product family, a decision framework, governance and licensing strategy, then Desktop versus Service. Establishes which edition and workflow fit your situation. - **Early–Middle (~27%–51%)**: The data-preparation core—connecting to local, relational, non-relational, JSON, and online sources; storage modes; cleansing and transforming in Power Query; then building and perfecting the semantic model (schemas, relationships, cardinality, aggregations). - **Middle (~51%–61%)**: Visualization and delivery—choosing and formatting visuals, building dashboards with tiles, themes, alerts, and subscriptions, then managing workspaces, apps, permissions, and usage metrics. - **Late (~61%–73%)**: The programming and platform layer—DAX fundamentals (data types, operators, calculated columns versus measures, parameters) plus integration with Power Apps, SharePoint, Power Automate, Teams, Dynamics 365, and Microsoft Fabric. - **Ending (~73%–100%)**: Operational and ecosystem material—tenant management, deployment concerns, customization and theming, and a curated resource list (Microsoft Learn, forums, podcasts, GitHub samples, conferences). Excerpts do not detail every late chapter. 【Key Takeaways】 - **Power BI is a pipeline, not a single screen** (Early): the book's spine is connect → transform → model → visualize → share → govern. Understanding this order prevents the common mistake of jumping straight to charts. - **Licensing and governance decisions come early** (Early): version choice, decision frameworks, and licensing strategy are treated as prerequisites, not afterthoughts—because they constrain what you can build and share. - **Data preparation is where most of the work lives** (Early–Middle): Power Query coverage spans source types, storage modes, error handling, and cleansing, with Copilot assisting anomaly detection and query optimization. - **The semantic model is the analytical engine** (Middle): star/snowflake/hybrid schemas, relationship cardinality and cross-filter direction, and aggregation design determine whether reports are fast and correct. - **DAX is taught for non-programmers** (Late): operators, data types, and the calculated-column-versus-measure distinction are introduced gently, framed as the language behind the visuals. - **Dashboards are operational artifacts** (Middle): tiles, themes, alerts, subscriptions, and mobile layouts turn reports into monitoring tools rather than static output. - **Collaboration and integration are first-class** (Late): workspaces, apps, permissions, and embedding into Teams, SharePoint, Power Automate, and Power Apps reflect how BI actually gets used inside organizations. - **This edition foregrounds AI and Fabric** (Late): Copilot for data quality and model simplification, plus Fabric dataflows, lakehouse, and Direct Lake mode, mark the biggest changes from the first edition. 【Reading Tips】 - **Skim Parts 1–2 if you already know BI concepts**; slow down at the semantic-model chapters (8–10), where most real-world quality problems originate. - **Read DAX (Part 4) with the tool open**—the column-versus-measure distinction only clicks through hands-on practice. - **Treat licensing and governance chapters as decision checklists**, not narrative; they answer "which version and how do we control it." - **Use the resource chapter as a launchpad** after finishing, since the book deliberately stops short of technical depth. - **Expect screenshot-heavy, step-by-step prose**; extract the workflow, not the click sequences. 【Coverage Limits】 This guide is built from stratified excerpts that are heavy on front matter, tables of contents, and figure lists; specific chapter arguments in the late sections (deployment, customization) are only partially visible, so details there are inferred from structure rather than full text.

Passage locations

Excerpt 1
e Choices: Power BI Versions Why Power BI Rather Than Excel?
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Excerpt 2
es: Power BI Versions Why Power BI Rather Than Excel?
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Excerpt 3
Part 4: Oh, No! There’s a Power BI Programming Language!
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Excerpt 4
b in Power BI Desktop. FIGURE 1-5: Locating your dashboards. FIGURE 1-6: The Navigation pane. Chapter 2 FIGURE 2-1: A prototype data lifecycle for an organiz...
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