{"id":116,"date":"2025-08-28T10:07:01","date_gmt":"2025-08-28T10:07:01","guid":{"rendered":"http:\/\/en.marcusm.dk\/bad_podcast\/?post_type=podcast&#038;p=116"},"modified":"2025-08-28T10:07:02","modified_gmt":"2025-08-28T10:07:02","slug":"graphframes-and-databricks-energinet-data-analysis","status":"publish","type":"podcast","link":"https:\/\/en.marcusm.dk\/bad_podcast\/podcast\/graphframes-and-databricks-energinet-data-analysis\/","title":{"rendered":"GraphFrames and Databricks: Energinet Data Analysis"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\">The provided texts discuss\u00a0<strong>GraphFrames<\/strong>\u00a0and\u00a0<strong>Databricks<\/strong>\u00a0as crucial technologies for data analysis, particularly within the context of\u00a0<strong>Energinet&#8217;s<\/strong>\u00a0evolving energy system. Energinet, facing the complexities of integrating renewable sources and phasing out conventional power plants, seeks to leverage these tools for\u00a0<strong>cost savings<\/strong>,\u00a0<strong>green transition<\/strong>, and\u00a0<strong>resilience<\/strong>. The sources aim to explain the technical aspects of both GraphFrames (for graph analytics with Apache Spark) and Databricks (as a platform for big data and machine learning), illustrating their potential to enhance\u00a0<strong>decision-making<\/strong>,\u00a0<strong>efficiency<\/strong>, and\u00a0<strong>innovation<\/strong>.<br><br>generated by Copilot<\/p>\n\n\n\n<div data-wp-interactive=\"core\/file\" class=\"wp-block-file\"><object data-wp-bind--hidden=\"!state.hasPdfPreview\" hidden class=\"wp-block-file__embed\" data=\"http:\/\/en.marcusm.dk\/bad_podcast\/wp-content\/uploads\/2025\/08\/GraphFrames-and-Databricks.pdf\" type=\"application\/pdf\" style=\"width:100%;height:600px\" aria-label=\"Embed GraphFrames and Databricks.\"><\/object><a id=\"wp-block-file--media-e22df647-ccd2-413e-b9a3-58d630ffb55d\" href=\"http:\/\/en.marcusm.dk\/bad_podcast\/wp-content\/uploads\/2025\/08\/GraphFrames-and-Databricks.pdf\">GraphFrames and Databricks<\/a><a href=\"http:\/\/en.marcusm.dk\/bad_podcast\/wp-content\/uploads\/2025\/08\/GraphFrames-and-Databricks.pdf\" class=\"wp-block-file__button wp-element-button\" download aria-describedby=\"wp-block-file--media-e22df647-ccd2-413e-b9a3-58d630ffb55d\">Download<\/a><\/div>\n","protected":false},"excerpt":{"rendered":"<p>The provided texts discuss\u00a0GraphFrames\u00a0and\u00a0Databricks\u00a0as crucial technologies for data analysis, particularly within the context of\u00a0Energinet&#8217;s\u00a0evolving energy system. Energinet, facing the complexities of integrating renewable sources and phasing out conventional power plants, seeks to leverage these tools for\u00a0cost savings,\u00a0green transition, and\u00a0resilience. The sources aim to explain the technical aspects of both GraphFrames (for graph analytics with Apache [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"inline_featured_image":false,"episode_type":"audio","audio_file":"http:\/\/en.marcusm.dk\/bad_podcast\/wp-content\/uploads\/2025\/08\/Powering_the_Future__How_Energinet_Uses_GraphFrames_and_Databricks_for_a_Resilient_Green_Grid.m4a","cover_image":"","cover_image_id":"","duration":"17:15","filesize":"31.76M","date_recorded":"2025-08-28 10:07:01","explicit":"","block":"","itunes_episode_number":"","itunes_title":"","itunes_season_number":"","itunes_episode_type":"","filesize_raw":"33300872"},"tags":[],"series":[10],"class_list":["post-116","podcast","type-podcast","status-publish","hentry","series-digital-accelerations-podcast"],"episode_featured_image":false,"episode_player_image":"https:\/\/en.marcusm.dk\/bad_podcast\/wp-content\/uploads\/2025\/08\/image-3.png","download_link":"https:\/\/en.marcusm.dk\/bad_podcast\/podcast-download\/116\/graphframes-and-databricks-energinet-data-analysis","player_link":"https:\/\/en.marcusm.dk\/bad_podcast\/podcast-player\/116\/graphframes-and-databricks-energinet-data-analysis","audio_player":"<a class=\"wp-embedded-audio\" href=\"https:\/\/en.marcusm.dk\/bad_podcast\/podcast-player\/116\/graphframes-and-databricks-energinet-data-analysis\">https:\/\/en.marcusm.dk\/bad_podcast\/podcast-player\/116\/graphframes-and-databricks-energinet-data-analysis<\/a>","episode_data":{"playerMode":"dark","subscribeUrls":{"apple_podcasts":{"key":"apple_podcasts","url":"","label":"Apple Podcasts","class":"apple_podcasts","icon":"apple-podcasts.png"},"stitcher":{"key":"stitcher","url":"","label":"Stitcher","class":"stitcher","icon":"stitcher.png"},"google_podcasts":{"key":"google_podcasts","url":"","label":"Google Podcasts","class":"google_podcasts","icon":"google-podcasts.png"},"spotify":{"key":"spotify","url":"","label":"Spotify","class":"spotify","icon":"spotify.png"}},"rssFeedUrl":"https:\/\/en.marcusm.dk\/bad_podcast\/feed\/podcast\/digital-accelerations-podcast","embedCode":"<blockquote class=\"wp-embedded-content\" data-secret=\"fwiYdzHiJC\"><a href=\"https:\/\/en.marcusm.dk\/bad_podcast\/podcast\/graphframes-and-databricks-energinet-data-analysis\/\">GraphFrames and Databricks: Energinet Data Analysis<\/a><\/blockquote><iframe sandbox=\"allow-scripts\" security=\"restricted\" src=\"https:\/\/en.marcusm.dk\/bad_podcast\/podcast\/graphframes-and-databricks-energinet-data-analysis\/embed\/#?secret=fwiYdzHiJC\" width=\"500\" height=\"350\" title=\"&#8220;GraphFrames and Databricks: Energinet Data Analysis&#8221; &#8211; Digital Accelerations Podcast-feed\" data-secret=\"fwiYdzHiJC\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\" class=\"wp-embedded-content\"><\/iframe><script>\n\/*! 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