{"id":4132,"date":"2026-09-09T08:25:58","date_gmt":"2026-09-09T08:25:58","guid":{"rendered":"https:\/\/simplemdg.com\/?post_type=events&#038;p=4132"},"modified":"2026-09-18T10:36:48","modified_gmt":"2026-09-18T10:36:48","slug":"simplemdg-at-big-data-ldn-2026","status":"publish","type":"events","link":"https:\/\/simplemdg.com\/beta\/events\/simplemdg-at-big-data-ldn-2026\/","title":{"rendered":"SimpleMDG at Big Data LDN 2026"},"content":{"rendered":"<div class=\"blog-context-colunm\">\n<p>For enterprise data and AI leaders, the challenge is no longer proving that AI can create value. It is ensuring the data behind AI, agents and automation is trusted, governed and consistent enough to support reliable execution at scale.<\/p>\n<p>Most enterprise data landscapes are still fragmented across SAP and non-SAP systems, with disconnected governance processes and unclear ownership. These gaps create risk when AI models, agents and automated workflows begin relying on that data for decisions and execution. SimpleMDG addresses this through data quality, consolidation, governed workflows and cross-system integration.  <\/p>\n<p>Meet SimpleMDG at Big Data LDN to explore how to operationalise a trusted data strategy for AI. We can assess how to establish the enterprise data foundation required for AI models, agents and automation, while embedding governance as a continuous operating discipline that sustains data reliability as the business scales. <\/p>\n<p class=\"listline\"><strong>Meet Our Experts To: <\/strong><\/p>\n<ul class=\"ul-list\">\n<li><strong>Establish Trusted Data for AI <\/strong><br \/>\nBuild a reliable enterprise data foundation through continuous validation, data quality, consolidation and golden-record management. <\/li>\n<li><strong>Operationalize Governance at Scale<\/strong> <br \/>\nEmbed no-code workflows, business rules and intelligent automation into ongoing governance processes while maintaining control and traceability. <\/li>\n<li><strong>Connect Enterprise Data for AI<\/strong> <br \/>\nGovern data consistently across SAP and non-SAP systems so AI models, agents, analytics and automation can operate on trusted enterprise data<\/li>\n<\/ul>\n<\/div>\n<div class=\"f-col present-people-col\">\n<h3 class=\"h3-title typo--light\">Connect with our team <\/h3>\n<div class=\"f-row s-gap48 team-listing-present\">\n<div class=\"team-member\">\n<img decoding=\"async\" src=\"\/wp-content\/uploads\/2025\/10\/mark.png\" alt=\"Mark Fletcher \" class=\"team-photo\"><\/p>\n<div class=\"team-info\">\n<h4 class=\"info-h4\">Mark Fletcher <\/h4>\n<p class=\"caption\">UK, Northern & Middle Europe<\/p>\n<p class=\"caption\"><a href=\"https:\/\/www.linkedin.com\/in\/mark-fletcher-a279ab31\/\" target=\"_blank\" rel=\"noopener\">Connect on LinkedIn<\/a><\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>For enterprise data and AI leaders, the challenge is no longer proving that AI can create value. It is ensuring the data behind AI, agents and automation is trusted, governed and consistent enough to support reliable execution at scale. Most enterprise data landscapes are still fragmented across SAP and non-SAP systems, with disconnected governance processes [&hellip;]<\/p>\n","protected":false},"featured_media":4133,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"Events\/Event-Single-Template-B.php","class_list":["post-4132","events","type-events","status-publish","has-post-thumbnail","hentry","event_tag-uki","event_year-uki"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.1 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>SimpleMDG at Big Data LDN 2026 - SimpleMDG<\/title>\n<meta name=\"robots\" content=\"noindex, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"SimpleMDG at Big Data LDN 2026 - SimpleMDG\" \/>\n<meta property=\"og:description\" content=\"For enterprise data and AI leaders, the challenge is no longer proving that AI can create value. 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