DataGalaxy

𝗖𝗵𝗼𝗼𝘀𝗶𝗻𝗴 𝘁𝗵𝗲 𝘄𝗿𝗼𝗻𝗴 𝗱𝗮𝘁𝗮 𝗰𝗮𝘁𝗮𝗹𝗼𝗴 𝘄𝗶𝗹𝗹 𝗰𝗼𝘀𝘁 𝘆𝗼𝘂. Don’t get locked into hidden fees, clunky interfaces, or a tool that doesn’t scale. We’ve benchmarked 12 leading solutions side-by-side — including Atlan, Collibra, Informatica, Purview, and more — so you can find the one that fits your goals, team, and stack. Inside the 2026 Comparison Guide: - Feature-by-feature product grid - Pricing factors (and hidden costs) - Vendor strengths & weaknesses - G2 Grid analysis ⬇️ Download the free guide and make your shortlist with confidence.

𝗖𝗵𝗼𝗼𝘀𝗶𝗻𝗴 𝘁𝗵𝗲 𝘄𝗿𝗼𝗻𝗴 𝗱𝗮𝘁𝗮 𝗰𝗮𝘁𝗮𝗹𝗼𝗴 𝘄𝗶𝗹𝗹 𝗰𝗼𝘀𝘁 𝘆𝗼𝘂. Don’t get locked into hidden fees, clunky interfaces, or a tool that doesn’t scale. We’ve benchmarked 12 leading solutions side-by-side — including Atlan, Collibra, Informatica, Purview, and more — so you can find the one that fits your goals, team, and stack. Inside the 2026 Comparison Guide: - Feature-by-feature product grid - Pricing factors (and hidden costs) - Vendor strengths & weaknesses - G2 Grid analysis ⬇️ Download the free guide and make your shortlist with confidence.

Every Solvency II reporting cycle, your team gets pulled off the roadmap to rebuild documentation and reconcile sources by hand for the QRT and SFCR. Same scramble, every quarter. DataGalaxy keeps that documentation current automatically, so each cycle starts with the evidence already in place and your people stay on the work that moves the data org forward.

Solvency II judges the data behind your SCR and MCR on three things: accuracy, completeness, and appropriateness. When your team can't show all three, the business holds extra prudential margin to cover the doubt, and that capital sits idle. DataGalaxy puts quality indicators right on your critical data, so your team can evidence what's behind the numbers and help free that margin.

📌 A Swiss Life data governance success story 📌 Solvency II. GDPR. A data team that couldn't align IT, business, and external partners on a shared data language. Learn from the team who solved it. Download the full 13-page case study.

💡 La plupart des webinaires vous disent que l'IA a besoin de « bonnes données ». Celui-ci est plus précis. Les agents IA ont besoin de trois couches distinctes — métadonnées, sémantique et ontologie — et la plupart des organisations en manquent au moins une. 🎙️ Charlotte Ledoux, experte en gouvernance Data & IA et intervenante invitée, décrypte ce sujet aux côtés de Laurent Dresse, Chief Evangelist chez DataGalaxy. Repartez avec un cadre de référence clair — et un diagnostic en 5 questions à appliquer dès le lundi suivant. 🗂️ 📅 Métadonnées, sémantique, ontologie : la pile de contexte qui fiabilise vos agents IA 🗓️ 17 juin 2026 | 🕐 11h00 CEST | 💻 En ligne | Gratuit → Inscrivez-vous ci-dessous.