{"version":"1.0","provider_name":"Conclusion Intelligence","provider_url":"https:\/\/conclusionintelligence.de\/nl","author_name":"Agita","author_url":"https:\/\/conclusionintelligence.de\/nl\/author\/agita-putri","title":"Why you should combine Data Mesh with Microsoft Fabric - Conclusion Intelligence","type":"rich","width":600,"height":338,"html":"<blockquote class=\"wp-embedded-content\" data-secret=\"QrfHFzruoF\"><a href=\"https:\/\/conclusionintelligence.de\/nl\/blog-nl-2\/combine-data-mesh-with-fabric\">Why you should combine Data Mesh with Microsoft Fabric<\/a><\/blockquote><iframe sandbox=\"allow-scripts\" security=\"restricted\" src=\"https:\/\/conclusionintelligence.de\/nl\/blog-nl-2\/combine-data-mesh-with-fabric\/embed#?secret=QrfHFzruoF\" width=\"600\" height=\"338\" title=\"&#8220;Why you should combine Data Mesh with Microsoft Fabric&#8221; &#8212; Conclusion Intelligence\" data-secret=\"QrfHFzruoF\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\" class=\"wp-embedded-content\"><\/iframe><script>\n\/*! This file is auto-generated *\/\n!function(d,l){\"use strict\";l.querySelector&&d.addEventListener&&\"undefined\"!=typeof URL&&(d.wp=d.wp||{},d.wp.receiveEmbedMessage||(d.wp.receiveEmbedMessage=function(e){var t=e.data;if((t||t.secret||t.message||t.value)&&!\/[^a-zA-Z0-9]\/.test(t.secret)){for(var s,r,n,a=l.querySelectorAll('iframe[data-secret=\"'+t.secret+'\"]'),o=l.querySelectorAll('blockquote[data-secret=\"'+t.secret+'\"]'),c=new RegExp(\"^https?:$\",\"i\"),i=0;i<o.length;i++)o[i].style.display=\"none\";for(i=0;i<a.length;i++)s=a[i],e.source===s.contentWindow&&(s.removeAttribute(\"style\"),\"height\"===t.message?(1e3<(r=parseInt(t.value,10))?r=1e3:~~r<200&&(r=200),s.height=r):\"link\"===t.message&&(r=new URL(s.getAttribute(\"src\")),n=new URL(t.value),c.test(n.protocol))&&n.host===r.host&&l.activeElement===s&&(d.top.location.href=t.value))}},d.addEventListener(\"message\",d.wp.receiveEmbedMessage,!1),l.addEventListener(\"DOMContentLoaded\",function(){for(var e,t,s=l.querySelectorAll(\"iframe.wp-embedded-content\"),r=0;r<s.length;r++)(t=(e=s[r]).getAttribute(\"data-secret\"))||(t=Math.random().toString(36).substring(2,12),e.src+=\"#?secret=\"+t,e.setAttribute(\"data-secret\",t)),e.contentWindow.postMessage({message:\"ready\",secret:t},\"*\")},!1)))}(window,document);\n\/\/# sourceURL=https:\/\/conclusionintelligence.de\/wp-includes\/js\/wp-embed.min.js\n<\/script>\n","thumbnail_url":"https:\/\/conclusionintelligence.de\/wp-content\/uploads\/2025\/12\/big-data-concept-digital-data-flow-transferring-generative-ai-scaled.jpg","thumbnail_width":2560,"thumbnail_height":1435,"description":"For many years, organizations relied heavily on centralized data warehouses and data lakes to support analytics. These architectures worked well when data volumes were modest and business demands predictable. Today, however, companies operate in a landscape defined by rapidly increasing data sources, complex domain-specific requirements, and rising regulatory pressure."}