{"id":1580,"date":"2026-11-09T23:21:05","date_gmt":"2026-11-09T20:21:05","guid":{"rendered":"https:\/\/ozgurveri.com\/?page_id=1580"},"modified":"2026-11-10T21:39:12","modified_gmt":"2026-11-10T18:39:12","slug":"ai-copilot-readiness","status":"publish","type":"page","link":"https:\/\/ozgurveri.com\/en\/hizmetler\/ai-copilot-readiness\/","title":{"rendered":"AI & Copilot Readiness"},"content":{"rendered":"
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AI & Copilot Readiness<\/h1>\n

To get reliable results from Microsoft Copilot, Fabric and enterprise AI, your data model, KPI definitions, relationships and security model need to be ready for AI-driven analytics.<\/span><\/p>\n

Request an AI Readiness Assessment<\/span><\/a><\/p>\n<\/div>\n

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\"AI<\/a><\/p>\n

Click the image to enlarge<\/span><\/div>\n

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The Right Foundation<\/span><\/h4>\n

AI Is Only as Reliable as the Data Model It Works With<\/span><\/h2>\n

Incomplete business definitions, ambiguous KPIs, incorrect relationships and uncontrolled access can lead to unreliable AI-assisted analysis.<\/span><\/p>\n<\/div>\n<\/div>\n<\/div>\n

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Semantic Model Review<\/span><\/h4>\n

Assess whether tables, relationships, measures and business logic are understandable and usable by AI.<\/span><\/p>\n<\/div>\n<\/div>\n

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Business Terminology<\/span><\/h4>\n

Align KPI, field and measure definitions with the terminology used by the business.<\/span><\/p>\n<\/div>\n<\/div>\n

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Security & Governance<\/span><\/h4>\n

Review RLS, access boundaries and data sensitivity in the context of AI use cases.<\/span><\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n

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Assessment Scope<\/span><\/h4>\n

Prepare Your Data Platform Before Scaling AI Usage<\/span><\/h2>\n<\/div>\n<\/div>\n<\/div>\n
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Technical Readiness<\/span><\/h4>\n

Review data quality, model relationships, DAX measures, performance, naming, descriptions, RLS and source dependencies.<\/span><\/p>\n<\/div>\n

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Business Readiness<\/span><\/h4>\n

Define which questions AI should answer, which KPIs matter and which business terminology users rely on.<\/span><\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n

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1. Current State<\/span><\/h4>\n

Review the existing BI and semantic model architecture.<\/span><\/p>\n<\/div>\n

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2. Readiness Analysis<\/span><\/h4>\n

Identify data, modelling and governance gaps that limit reliable AI usage.<\/span><\/p>\n<\/div>\n

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3. Implementation Plan<\/span><\/h4>\n

Prioritise improvements and define pilot AI use cases.<\/span><\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n

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How Ready Is Your Data Platform for AI?<\/span><\/h2>\n

Let’s assess your current Power BI and data platform to identify what needs to change before AI and Copilot adoption.<\/span><\/p>\n<\/div>\n

Talk to Us<\/span><\/a><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>","protected":false},"excerpt":{"rendered":"

Power BI ve veri platformunuzu Microsoft Copilot ve kurumsal AI kullan\u0131m\u0131na haz\u0131rlamak i\u00e7in semantic model, veri kalitesi, i\u015f terminolojisi ve g\u00fcvenlik de\u011ferlendirmesi.<\/p>","protected":false},"author":1,"featured_media":0,"parent":104,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"page-templates\/pages.php","meta":{"_jetpack_hide_featured_image":false,"_jetpack_featured_image_duplicate_dismissed":0,"footnotes":""},"class_list":["post-1580","page","type-page","status-publish","hentry"],"aioseo_notices":[],"aioseo_head":"\n\t\t\n\t\n\t\n\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t