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Bugsnag, plus a replay tool, plus an analytics tool. Three vendors, three SDKs, three security reviews, and you're still strugging to stitch the timeline together by hand. Not anymore.

Technology alone doesn't create operational strength. Assess how well your people, processes, and decision workflows work together to improve resilience before the next high-impact weather event.

AI gets more useful when it can securely access your data and take action. Build governed AI agents that connect your data, automate workflows, and get real work done.

Raw data isn't ready for analytics or AI. Domo helps you get it there faster. Clean, combine, and prepare data for AI with intuitive tools, SQL, or Python.

Move beyond reactive troubleshooting. Learn how to approach SLOs, reliability, and production debugging with insights from Liz Fong-Jones, Honeycomb Technical Fellow and an SRE with over 20 years of experience. Get the second edition free.

A dropped Unity Catalog managed table can sit in a recovery period of up to 30 days, and storage billing continues the whole time. Download this guide and learn: • How to configure the recovery period at the catalog or schema level • What actually happens to the files once that window ends • When a shorter recovery period makes sense for temporary tables

Spending hours double-checking every number before a report goes out? Learn to analyze and report with AI on data you can trust, in 30 minutes. Each session in the Databox webinar series walks you through a specific reporting or analysis task with AI Analyst, so you leave with something you can apply that same day. Upcoming live: → Oct 28: How to connect Claude to Databox and create a report in minutes → Nov 10: How to analyze performance across all your client accounts in one conversation Watch on demand: ✓ The Agentic Era: How teams will use data to improve performance in 2027 ✓ Building a Marketing Dashboard in One Conversation ✓ How to Answer Any Performance Question in 5 Minutes with AI Analyst Register once for the whole series: https://lnkd.in/duZ4sxpJ/?utm_campaign=WinboxFullFunnelAds%255BAgency%255D&utm_source=linkedin&utm_medium=paid&utm_id=731734533&hsa_acc=513446957&hsa_cam=731734533&hsa_grp=361908443&hsa_ad=1584650053&hsa_net=linkedin&hsa_ver=3

Spending hours double-checking every number before a report goes out? Learn to analyze and report with AI on data you can trust, in 30 minutes. Each session in the Databox webinar series walks you through a specific reporting or analysis task with AI Analyst, so you leave with something you can apply that same day. Upcoming live: → Oct 28: How to connect Claude to Databox and create a report in minutes → Nov 10: How to analyze performance across all your client accounts in one conversation Watch on demand: ✓ The Agentic Era: How teams will use data to improve performance in 2027 ✓ Building a Marketing Dashboard in One Conversation ✓ How to Answer Any Performance Question in 5 Minutes with AI Analyst Register once for the whole series: https://lnkd.in/duZ4sxpJ/?utm_campaign=WinboxFullFunnelAds%255BCompanies%255D&utm_source=linkedin&utm_medium=paid&utm_id=731770343&hsa_acc=513446957&hsa_cam=731770343&hsa_grp=361909283&hsa_ad=1584659993&hsa_net=linkedin&hsa_ver=3

Point-to-point pipelines don’t scale. Learn how Kafka decouples telemetry from the tools that consume it.

Telemetry volumes keep growing. See how platform teams stream it with Kafka instead of shipping it point to point.

It only takes one gap in your protection for recent transactions to be at risk. With StandbyMP Zero Data Loss, continuous redo streaming runs alongside archive log shipping to reduce that exposure to sub-second levels.

Ekai builds your semantic layer for you: governed models plus production dbt, verified against your warehouse, in hours instead of months. See it in 30 minutes and we’ll send you AirPods. Fit or not. 🎧

💸 Do you know where your AI tokens actually go? AI in production is billed in tokens, and agentic tasks can consume 5 to 30 times more than a standard chatbot exchange. Hidden reasoning, bloated context, and looping agents drive up costs that finance sees on the invoice but no one can explain. In this whitepaper, discover how AI observability makes token spend visible and controllable. You'll learn the six drivers that quietly inflate AI bills, five proven levers to cut costs without sacrificing output quality, and an ROI model you can adapt to your own numbers. Most teams can reduce AI spend by 30 to 50% once they can finally measure it.

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How much time would you and your HR team get back if onboarding and your ticket queue ran themselves? Find out live on Oct 22. Join this event, and you'll learn how to build an agent that: - Ramps new hires faster - Clears transactional tasks off your plate - Holds onto knowledge instead of losing it You can come with your toughest People problem, and leave with a specialized agent to share with your entire team. Register now to experience multiplayer AI on your own data.

𝗞𝗼𝘀𝘁𝗲𝗻𝗳𝗿𝗲𝗶𝗲𝘀 𝗪𝗲𝗯𝗶𝗻𝗮𝗿: 𝗪𝗶𝗲 𝗸ö𝗻𝗻𝗲𝗻 𝗦𝘁𝗮𝗱𝘁𝘄𝗲𝗿𝗸𝗲 𝘂𝗻𝗱 𝗩𝗲𝗿𝘀𝗼𝗿𝗴𝗲𝗿 𝗺𝗲𝗵𝗿 𝗮𝘂𝘀 𝗶𝗵𝗿𝗲𝗻 𝗗𝗮𝘁𝗲𝗻 𝗺𝗲𝗵𝗿 𝗺𝗮𝗰𝗵𝗲𝗻 – 𝘁𝗿𝗼𝘁𝘇 𝗸𝗻𝗮𝗽𝗽𝗲𝗿 𝗣𝗲𝗿𝘀𝗼𝗻𝗮𝗹𝗿𝗲𝘀𝘀𝗼𝘂𝗿𝗰𝗲𝗻? Stadtwerke und Versorger haben heute mehr Daten zur Verfügung als je zuvor, um die richtigen strategischen und operativen Entscheidungen zu treffen – und gleichzeitig immer weniger Experten, um sie auszuwerten. Wie lässt sich dieses Dilemma lösen? Was braucht es, damit Daten besser eingesetzt werden können, sowohl im Tagesgeschäft als auch in der langfristigen Planung? Im kostenfreien Webinar 𝗦𝘁𝗮𝗱𝘁𝘄𝗲𝗿𝗸𝗲 𝗹𝗶𝘃𝗲: 𝗪𝗮𝘀 𝗳𝘂𝗻𝗸𝘁𝗶𝗼𝗻𝗶𝗲𝗿𝘁, 𝘄𝗼 𝗱𝗶𝗲 𝗛ü𝗿𝗱𝗲𝗻 𝗹𝗶𝗲𝗴𝗲𝗻 𝘂𝗻𝗱 𝘄𝗲𝗹𝗰𝗵𝗲 𝗘𝗿𝗳𝗼𝗹𝗴𝗲 𝗺ö𝗴𝗹𝗶𝗰𝗵 𝘀𝗶𝗻𝗱 geben Torsten Brauer, Leiter Business Development bei Disy, und Florian Schwarz, Leiter Netzdatenmanagement bei der Stadtwerke Karlsruhe Netzservice GmbH, einen offenen Einblick in die Praxis. 𝗧𝗲𝗿𝗺𝗶𝗻: 𝟮𝟳. 𝗢𝗸𝘁𝗼𝗯𝗲𝗿 | 𝟭𝟰:𝟬𝟬 𝗯𝗶𝘀 𝟭𝟱:𝟬𝟬 𝗨𝗵𝗿 Im Webinar zeigen wir: • wie Stadtwerke und Versorger ihre vorhandenen Daten einfacher und direkt für schnelle Auswertungen und Berichte nutzen können • versorgungsrelevante Anwendungsfälle und den Mehrwert einer plattformbasierten Datenanalyse • wo Hürden liegen und die entstandenen Erkenntnisse 𝗔𝘀𝗸 𝗺𝗲 𝗔𝗻𝘆𝘁𝗵𝗶𝗻𝗴: Im Anschluss beantwortet Florian Schwarz Ihre Fragen direkt aus der Praxis. Fragen können gerne schon vorab eingereicht werden. Jetzt kostenfrei anmelden: https://lnkd.in/gu9xYsYS/?utm_campaign=Stadtwerke2026-Website-Conversion-StadtwerkeLandingpage-CoreTargets&utm_source=linkedin&utm_medium=paid&utm_id=932604056&hsa_acc=509002823&hsa_cam=932604056&hsa_grp=912126246&hsa_ad=1642039116&hsa_net=linkedin&hsa_ver=3

We looked at how 52,771 Snowflake companies get data into Snowflake. → 12.7% run Fivetran → 7.9% run Azure Data Factory → 6.5% run Informatica → 2.7% run AWS Glue → 2.7% run Airbyte → 1.5% run Matillion Very surprised to not see folks like Estuary or Streamkap up there! Source: Crustdata (YC F24)

We've normalized running two expensive warehouses before we've normalized running one expensive warehouse and one cheap one. 54.5% of Snowflake companies also use Databricks. Just 2.3% use DuckDB alongside Snowflake. So the barrier clearly isn’t “we don’t want another execution engine.” The interesting question is why it’s still unusual to route the right workloads somewhere dramatically cheaper. Source: Crustdata (YC F24)

We’re heading to Tallinn Data Week in Estonia on Thursday, 22 October (Also a satellite event!) Most data projects don’t fail because of the tech. They fail because the business context never makes it into the data. In three hours we’ll show a different approach: → Why human-led, AI-assisted context engineering beats handing everything to AI coding agents → A live demo of Ekai going from raw data to AI agents in hours instead of months → Automated business logic migration from Qlik Sense to Snowflake, with Infotrust → An instructor-led walkthrough, plus trial access so you can take Ekai home with you Tero Miikki, our Chief Commercial Officer & Global Partnership Lead, and Hussnain Ahmed, our Co-founder & Chief AI Officer, will be there. If you’re attending Tallinn Data Week, or you’ll be in Tallinn that day, send them a message. They’d love to grab a coffee and hear what you’re working on. 📍 ibis Tallinn Center, Tallinn, Estonia 🗓️ Thursday, 22 October · 10:00–13:00 🎟️ Free. Coffee and light snacks provided. Register: https://lnkd.in/dHBXgquE #TallinnDataWeek #DataProducts #Snowflake #AI #SemanticLayer

Tighter RPO doesn’t have to mean moving to Oracle Enterprise Edition. StandbyMP Zero Data Loss brings sub-second data protection to Oracle Standard Edition, helping you protect more of your latest transactions while staying on SE.

L'IA sait raisonner. Pourtant, elle hallucine encore dès qu'elle ne comprend pas le contexte des données qu'elle utilise. La raison ? Il ne lui manque pas des données, mais du contexte. Vos collaborateurs expérimentés savent quelle donnée utiliser, quand, et avec quelles précautions. Vos agents IA, eux, partent de zéro.

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Pour une IA agentique fiable, la qualité des données ne suffit plus. Elles doivent aussi être porteuses de sens, connectées, à jour et actionnables dans leur contexte. C'est tout l'enjeu du context engineering, qui repose sur trois piliers : la connectivité (MCP, APIs), la valeur métier des data products et une couche de contexte dynamique. Dans cet ebook : → le Living Context Layer, la pièce manquante d'une donnée AI-ready ; → comment la data product marketplace capte les signaux d'usage en temps réel ; → comment Huwise fournit ce contexte à vos agents IA.