<?xml version="1.0" encoding="UTF-8"?><rss xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:atom="http://www.w3.org/2005/Atom" version="2.0"><channel><title><![CDATA[Supply Chain Flow]]></title><description><![CDATA[Data Flow Analysis
Logistics Flow Analysis
Supply Chain Flow Analysis]]></description><link>https://jihwanpowerbifabric.wixsite.com/supplychainflow/blog</link><generator>RSS for Node</generator><lastBuildDate>Sun, 06 Sep 2026 02:58:06 GMT</lastBuildDate><atom:link href="https://jihwanpowerbifabric.wixsite.com/supplychainflow/blog-feed.xml" rel="self" type="application/rss+xml"/><item><title><![CDATA[Q&#38;A Deprecation and the Hidden DevOps Challenge: Where Do AI Instructions Actually Live?]]></title><description><![CDATA[In this writing, I want to share what I learned while exploring the Prep Data for AI  feature in Power BI Desktop — and why it matters far more for DevOps workflows than I initially expected. Microsoft recently announced the deprecation of Power BI Q&#38;A by December 2026 , directing users toward Copilot as the replacement. The reasoning is straightforward: consolidate natural language capabilities into a single, more advanced experience. But as I dug deeper, I found an architectural question...]]></description><link>https://jihwanpowerbifabric.wixsite.com/supplychainflow/post/q-a-deprecation-and-the-hidden-devops-challenge-where-do-ai-instructions-actually-live</link><guid isPermaLink="false">6958b285bd1cfb4bde77f256</guid><category><![CDATA[Power BI]]></category><pubDate>Sat, 03 Jan 2026 07:04:54 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/64d1a1_e004d34840ac4b9c8ed50c623110d419~mv2.png/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>Jihwan Kim</dc:creator></item><item><title><![CDATA[Why PBIR Becoming Default in Jan 2026 is a Milestone]]></title><description><![CDATA[In this writing, I like to share how I started to learn about the most significant architectural shift in Power BI's history: the transition to the Power BI Enhanced Report Format (PBIR) . For years, I as a Power BI developer have lived in the era of the .pbix  file. It served me well as a container, but it had one fatal flaw: it was a "black box." A binary blob that defied version control, made collaboration a nightmare of "save as" copies, and locked my logic inside a proprietary format....]]></description><link>https://jihwanpowerbifabric.wixsite.com/supplychainflow/post/why-pbir-becoming-default-in-jan-2026-is-a-milestone</link><guid isPermaLink="false">694fcd79a4852561114e811e</guid><category><![CDATA[Power BI]]></category><pubDate>Sat, 27 Dec 2025 12:58:02 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/64d1a1_11531ab891d445c79a66a9b9c1488915~mv2.png/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>Jihwan Kim</dc:creator></item><item><title><![CDATA[How I Used Power BI Modeling MCP + PBIP to Build a Contoso Star Schema, Generate Measures, Clean Metadata, and Auto-Hide Visual Filters]]></title><description><![CDATA[In this writing, I want to share how I started to learn using the Power BI Modeling MCP server  together with Power BI Projects (.pbip) and VSCode , and how that experiment turned into a full workflow: building a Contoso  star schema with an AI agent, generating a measure table , cleaning up metadata  (Sort by column), and automatically hiding visual-level filters  in the filter pane by editing the report JSON. This is all from an actual hands-on session; the screenshots I’ll add are exactly...]]></description><link>https://jihwanpowerbifabric.wixsite.com/supplychainflow/post/how-i-used-power-bi-modeling-mcp-pbip-to-build-a-contoso-star-schema-generate-measures-clean-met</link><guid isPermaLink="false">692ae4659d72494dae9ff256</guid><category><![CDATA[Power BI]]></category><pubDate>Sat, 29 Nov 2025 13:02:24 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/64d1a1_bdfac87e3c3e483baa3e952a88b5abef~mv2.png/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>Jihwan Kim</dc:creator></item><item><title><![CDATA[Exploring the Power BI Modeling MCP Server: My Journey From Curiosity to a New Modeling Workflow]]></title><description><![CDATA[I didn’t expect the Power BI Modeling MCP Server to reshape my modeling habits. My plan was simple: read the November 2025 Feature Summary, test the feature for a few minutes, and move on. Instead, those “few minutes” turned into a fully immersive exploration where Copilot started behaving less like a text generator and more like a modeling agent. This post is a narrative of that journey — a story told through every screenshot I captured along the way — and how those moments connected to the...]]></description><link>https://jihwanpowerbifabric.wixsite.com/supplychainflow/post/exploring-the-power-bi-modeling-mcp-server-my-journey-from-curiosity-to-a-new-modeling-workflow</link><guid isPermaLink="false">6921b626644344a47710c77f</guid><category><![CDATA[Power BI]]></category><pubDate>Sat, 22 Nov 2025 13:56:35 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/64d1a1_57da7c7a2fbf40cab84f0401973704ad~mv2.png/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>Jihwan Kim</dc:creator></item><item><title><![CDATA[Using Microsoft Fabric Notebooks to Render an SVG Measure From a Semantic Model]]></title><description><![CDATA[In this writing, I’d like to share the small experiment I did recently: querying an SVG measure from a semantic model using a Fabric Notebook , scaling it with Python, and displaying it directly in the notebook output. The idea started from a question from my manager: “If the semantic model produces SVG via DAX, can we render it outside Power BI and reuse it somewhere else?” Once I tried it, new use cases started to appear. The Data Model I Used Below is the sample semantic model I used for...]]></description><link>https://jihwanpowerbifabric.wixsite.com/supplychainflow/post/using-microsoft-fabric-notebooks-to-render-an-svg-measure-from-a-semantic-model</link><guid isPermaLink="false">6919b5f40dbc57ddd09c8f83</guid><category><![CDATA[Power BI]]></category><category><![CDATA[Fabric]]></category><pubDate>Sun, 16 Nov 2025 13:18:25 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/64d1a1_eaedf603b6684b76a56757e08537a7b6~mv2.png/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>Jihwan Kim</dc:creator></item><item><title><![CDATA[Power BI Semantic Models as Accelerators for AI-Driven Insights]]></title><description><![CDATA[In this writing, I’d like to share how I started learning and experimenting with Copilot and AI-driven features  in Power BI and Fabric — and what I discovered about the role of semantic models  in making them work effectively. Prerequisites Before jumping into it, here’s the setup I used for experimenting with Copilot and AI-driven insights in Power BI and Fabric. Power BI Service (Fabric workspace)  — The experiments were all performed in a Fabric-enabled workspace, since Copilot  and...]]></description><link>https://jihwanpowerbifabric.wixsite.com/supplychainflow/post/power-bi-semantic-models-as-accelerators-for-ai-driven-insights</link><guid isPermaLink="false">690ef87e6509164f21b09ceb</guid><category><![CDATA[Power BI]]></category><category><![CDATA[Fabric]]></category><pubDate>Sat, 08 Nov 2025 12:27:25 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/64d1a1_280f7f20b04249eea22720a342b27341~mv2.png/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>Jihwan Kim</dc:creator></item><item><title><![CDATA[Understanding Composite Semantic Models with Direct Lake and Import Tables]]></title><description><![CDATA[In this writing, I’d like to share how I started learning about Composite Semantic Models  in Power BI and Fabric — especially now that Direct Lake mode can coexist with Import tables . When this feature first appeared in preview, I was curious how it could help simplify data architecture and improve performance for mixed workloads. After some testing, I’ve learned both the power and the limitations of this hybrid approach. Why This Feature Matters For years, I had to choose between Import...]]></description><link>https://jihwanpowerbifabric.wixsite.com/supplychainflow/post/understanding-composite-semantic-models-with-direct-lake-and-import-tables</link><guid isPermaLink="false">6905e41f07f57e4820897ec0</guid><category><![CDATA[Power BI]]></category><category><![CDATA[Fabric]]></category><pubDate>Sat, 01 Nov 2025 11:44:27 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/64d1a1_70db852df4454420bcdee7e51b2279ad~mv2.png/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>Jihwan Kim</dc:creator></item><item><title><![CDATA[Exploring DAX UDFs — Challenges, Learnings, and What Comes Next]]></title><description><![CDATA[In this writing, I’d like to share how I started to learn and create my own DAX UDF (User Defined Function) library , the pain points I’ve faced while trying to make the functions as general as possible, and how I plan to take the next steps forward. You can explore the project here: jihwankimdata/dax_udf_library How It Started Like many Power BI developers, I’ve written the same logic dozens of times — percentage growth, variance analysis, ranking, or window calculations — slightly...]]></description><link>https://jihwanpowerbifabric.wixsite.com/supplychainflow/post/exploring-dax-udfs-challenges-learnings-and-what-comes-next</link><guid isPermaLink="false">68fcc46b4cd3f117277adf34</guid><category><![CDATA[Power BI]]></category><pubDate>Sat, 25 Oct 2025 13:11:28 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/64d1a1_bbd10c6020f74098ad74e27870fa8cd4~mv2.png/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>Jihwan Kim</dc:creator></item><item><title><![CDATA[Reusable DAX logic with User Defined Functions (UDFs) – a new paradigm for semantic modeling]]></title><description><![CDATA[Introduction DAX User Defined Functions (UDFs) – introduced in the Power BI September 2025 release – let you encapsulate complex logic into named, parameterized functions that can be reused across measures and models.  Power BI September 2025 Feature Summary | Microsoft Power BI Blog | Microsoft Power BI Unlike calculation groups, UDFs accept parameters and nest other functions, paving the way for cleaner, more maintainable semantic models. Enterprise scenario:  Let's assume, I am responsible...]]></description><link>https://jihwanpowerbifabric.wixsite.com/supplychainflow/post/reusable-dax-logic-with-user-defined-functions-udfs-a-new-paradigm-for-semantic-modeling</link><guid isPermaLink="false">68f36aa950873aaf5db4212c</guid><pubDate>Sat, 18 Oct 2025 12:14:10 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/64d1a1_b524bf6f417b414dab97e55ad790fbce~mv2.png/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>Jihwan Kim</dc:creator></item><item><title><![CDATA[What TMDL View Means for Model Versioning &#38; Enterprise Workflows]]></title><description><![CDATA[In this writing, I’d like to share how I’ve been exploring TMDL (Tabular Model Definition Language)  since it was in preview — and why...]]></description><link>https://jihwanpowerbifabric.wixsite.com/supplychainflow/post/what-tmdl-view-means-for-model-versioning-enterprise-workflows</link><guid isPermaLink="false">68ea3fb8f99b368a71dd1865</guid><category><![CDATA[Power BI]]></category><pubDate>Sat, 11 Oct 2025 12:32:56 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/64d1a1_1c9238ddff5248cda6092cace5fd414a~mv2.png/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>Jihwan Kim</dc:creator></item><item><title><![CDATA[Editing Semantic Models in the Service + TMDL View &#38; Best Practices]]></title><description><![CDATA[In this writing, I’d like to share how I started learning to edit semantic models directly in the Power BI service  and how TMDL (Tabular...]]></description><link>https://jihwanpowerbifabric.wixsite.com/supplychainflow/post/editing-semantic-models-in-the-service-tmdl-view-best-practices</link><guid isPermaLink="false">68e0ea88fabe64c932f3635b</guid><category><![CDATA[Power BI]]></category><category><![CDATA[Fabric]]></category><pubDate>Sat, 04 Oct 2025 10:55:14 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/64d1a1_f194d26322964a0f8a902995f768e052~mv2.png/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>Jihwan Kim</dc:creator></item><item><title><![CDATA[Using Semantic Model Refresh Templates &#38; Fabric Data Pipelines for Scalable Model Maintenance]]></title><description><![CDATA[Why I Started Looking at Refresh Templates For years, I’ve learned and worked with refresh schedules in Power BI. At a small scale,...]]></description><link>https://jihwanpowerbifabric.wixsite.com/supplychainflow/post/using-semantic-model-refresh-templates-fabric-data-pipelines-for-scalable-model-maintenance</link><guid isPermaLink="false">68c8daf3d424f0454cc18122</guid><category><![CDATA[Fabric]]></category><pubDate>Sun, 21 Sep 2025 07:55:45 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/64d1a1_0b4cf0bf55d347309ad0302c653d46f6~mv2.png/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>Jihwan Kim</dc:creator></item><item><title><![CDATA[Stop Repeating DAX: Reusable Time Intelligence Calculation Group with TMDL]]></title><description><![CDATA[In this writing, I’d like to share how I've learned to dramatically accelerate one of the most common and repetitive tasks in Power BI...]]></description><link>https://jihwanpowerbifabric.wixsite.com/supplychainflow/post/stop-repeating-dax-reusable-time-intelligence-calculation-group-with-tmdl</link><guid isPermaLink="false">688f0eaf703020ba46e46594</guid><category><![CDATA[Power BI]]></category><pubDate>Sun, 03 Aug 2025 10:06:52 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/64d1a1_ba5951634cf1452aad365607510e6199~mv2.jpg/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>Jihwan Kim</dc:creator></item><item><title><![CDATA[Why Sunsetting Default Semantic Models is Fabric's Best Decision Yet]]></title><description><![CDATA[In this writing, I’d like to share what I have learned from a recent Microsoft Fabric announcement that, in my opinion, is one of the...]]></description><link>https://jihwanpowerbifabric.wixsite.com/supplychainflow/post/why-sunsetting-default-semantic-models-is-fabric-s-best-decision-yet</link><guid isPermaLink="false">6884c6fd53e1587dc0d6b87d</guid><category><![CDATA[Power BI]]></category><category><![CDATA[Fabric]]></category><pubDate>Sat, 26 Jul 2025 12:38:40 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/64d1a1_9c9b194bec534423940718e7925e628a~mv2.jpg/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>Jihwan Kim</dc:creator></item><item><title><![CDATA[DAX: Visual Calculations and Measures]]></title><description><![CDATA[In this writing, I’d like to share how I learn to navigate the evolving world of DAX. In an era dominated by AI and low-code solutions,...]]></description><link>https://jihwanpowerbifabric.wixsite.com/supplychainflow/post/dax-visual-calculations-and-measures</link><guid isPermaLink="false">687c87f53b808c020d55be21</guid><category><![CDATA[Power BI]]></category><pubDate>Sun, 20 Jul 2025 08:40:46 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/64d1a1_953de4a546464d03aaaf06df1cb201b0~mv2.jpg/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>Jihwan Kim</dc:creator></item><item><title><![CDATA[Taming the Beast: From 4-Hour Refreshes to Fast Insights with Power BI and Microsoft Fabric]]></title><description><![CDATA[I. Introduction: The All-Too-Common Incremental Refresh Headache In this writing, I’d like to share how I approach a frustratingly common...]]></description><link>https://jihwanpowerbifabric.wixsite.com/supplychainflow/post/taming-the-beast-from-4-hour-refreshes-to-fast-insights-with-power-bi-and-microsoft-fabric</link><guid isPermaLink="false">68736d2ae8e47f31f0d3a980</guid><category><![CDATA[Power BI]]></category><category><![CDATA[Fabric]]></category><pubDate>Sun, 13 Jul 2025 10:31:24 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/64d1a1_f3afb27b9f9c4c289e8190cc5cc7c20b~mv2.png/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>Jihwan Kim</dc:creator></item><item><title><![CDATA[.gitignore for Power BI Projects: A Simple Guide for the Modern BI Developer]]></title><description><![CDATA[In this writing, I’d like to share how I learned and understood one of the most important—and often overlooked—files I encountered as I...]]></description><link>https://jihwanpowerbifabric.wixsite.com/supplychainflow/post/gitignore-for-power-bi-projects-a-simple-guide-for-the-modern-bi-developer</link><guid isPermaLink="false">68690ad9241a1bcbebc6c7e0</guid><category><![CDATA[Power BI]]></category><pubDate>Sat, 05 Jul 2025 12:31:05 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/64d1a1_d692ae56da574e98a6bda05fc675930b~mv2.png/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>Jihwan Kim</dc:creator></item><item><title><![CDATA[Start Coding: A Modern Power BI Workflow with TMDL and VS Code]]></title><description><![CDATA[In this writing, I’d like to share how I am evolving my Power BI development process. For years, building semantic models has been a...]]></description><link>https://jihwanpowerbifabric.wixsite.com/supplychainflow/post/start-coding-a-modern-power-bi-workflow-with-tmdl-and-vs-code</link><guid isPermaLink="false">6860e7e0ccc85eb48d0e9fa2</guid><category><![CDATA[Power BI]]></category><pubDate>Sun, 29 Jun 2025 09:16:28 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/64d1a1_7b3b96d254e54c26abd1c14fa7aa4a30~mv2.png/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>Jihwan Kim</dc:creator></item><item><title><![CDATA[Leveraging OFFSET for Dynamic Ranking and Related Analytical Patterns Power BI: A Deep Dive Beyond Time Intelligence]]></title><description><![CDATA[In this writing, I like to share how I learned understanding and writing OFFSET DAX function in Power BI. OFFSET function (DAX) - DAX |...]]></description><link>https://jihwanpowerbifabric.wixsite.com/supplychainflow/post/leveraging-offset-for-dynamic-ranking-and-related-analytical-patterns-power-bi-a-deep-dive-beyond-t</link><guid isPermaLink="false">6857e399179fee421c339d0f</guid><category><![CDATA[Power BI]]></category><pubDate>Sun, 22 Jun 2025 12:14:51 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/64d1a1_c13233c5845f411695d1606a25757829~mv2.png/v1/fit/w_1000,h_768,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>Jihwan Kim</dc:creator></item><item><title><![CDATA[Unlocking Next-Level Productivity with Power BI's TMDL View and AI]]></title><description><![CDATA[Introduction: A New Chapter in My Power BI Development Journey In this writing, I'd like to share my journey with a feature that has...]]></description><link>https://jihwanpowerbifabric.wixsite.com/supplychainflow/post/unlocking-next-level-productivity-with-power-bi-s-tmdl-view-and-ai</link><guid isPermaLink="false">684d5c655a220fb240547bcd</guid><category><![CDATA[Power BI]]></category><pubDate>Sat, 14 Jun 2025 14:41:56 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/64d1a1_84206b30d7684fd3af76b775a092fdac~mv2.jpg/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>Jihwan Kim</dc:creator></item></channel></rss>