{"id":7364,"date":"2025-10-05T07:02:57","date_gmt":"2025-10-05T07:02:57","guid":{"rendered":"https:\/\/mailitics.com\/index.php\/2025\/10\/05\/real-time-intelligence-in-microsoft-fabric-the-ultimate-guide\/"},"modified":"2025-10-05T07:02:57","modified_gmt":"2025-10-05T07:02:57","slug":"real-time-intelligence-in-microsoft-fabric-the-ultimate-guide","status":"publish","type":"post","link":"https:\/\/mailitics.com\/index.php\/2025\/10\/05\/real-time-intelligence-in-microsoft-fabric-the-ultimate-guide\/","title":{"rendered":"Real-Time Intelligence in Microsoft Fabric: The Ultimate Guide"},"content":{"rendered":"<p>    Real-Time Intelligence in Microsoft Fabric: The Ultimate Guide<br \/>\n \t<BR><br \/>\n<BR><\/BR><br \/>\n    <!-- no image --><br \/>\n \t<BR><br \/>\n<BR><\/BR><\/p>\n<div>\n<p>Once upon a time, handling streaming data was considered an\u00a0avant-garde\u00a0approach. Since the introduction of relational database management systems in the 1970s and traditional data warehousing systems in the late 1980s, all data workloads began and ended with the so-called\u00a0batch processing. Batch processing relies on the concept of collecting numerous tasks in a group (or batch) [\u2026]<\/p>\n<p>The post <a href=\"https:\/\/towardsdatascience.com\/real-time-intelligence-in-microsoft-fabric-the-ultimate-guide\/\">Real-Time Intelligence in Microsoft Fabric: The Ultimate Guide<\/a> appeared first on <a href=\"https:\/\/towardsdatascience.com\/\">Towards Data Science<\/a>.<\/p>\n<\/div>\n<p> \t<BR><br \/>\n <BR><\/BR><br \/>\n    Nikola Ilic<br \/>\n \t<BR><br \/>\n<BR><\/BR><br \/>\n<a href=\"https:\/\/towardsdatascience.com\/real-time-intelligence-in-microsoft-fabric-the-ultimate-guide\/\">Go to original source<\/a><br \/>\n \t<BR><br \/>\n <BR><\/BR><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Real-Time Intelligence in Microsoft Fabric: The Ultimate Guide Once upon a time, handling streaming data was considered an\u00a0avant-garde\u00a0approach. Since the introduction of relational database management systems in the 1970s and traditional data warehousing systems in the late 1980s, all data workloads began and ended with the so-called\u00a0batch processing. Batch processing relies on the concept of [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[62,938,83,67,1158,3952],"tags":[84,3193,15],"class_list":["post-7364","post","type-post","status-publish","format-standard","hentry","category-aimldsaimlds","category-data-processing","category-data-science","category-deep-dives","category-microsoft-fabric","category-real-time-analytics","tag-data","tag-real","tag-time"],"_links":{"self":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts\/7364"}],"collection":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/comments?post=7364"}],"version-history":[{"count":0,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts\/7364\/revisions"}],"wp:attachment":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/media?parent=7364"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/categories?post=7364"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/tags?post=7364"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}