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Context is moving faster than any other layer of the AI stack. Formats, protocols, and standards are converging in real time, and what you build this quarter has to survive the next one. The open-interchange session at Context Conference is where that future gets argued: which open formats context is converging on, which objects become portable, and how your organization keeps its context open and owned while everything around it changes. Bob Muglia, Josh Klahr (Apache Ossie), and Prajakta Damle (Open Knowledge Format, Google), at one table. Virtual, October 28, free.

Let every team self-serve Kafka inside guardrails, without infrastructure and administration growing at the same rate as adoption.

NASA lost a spacecraft because one team sent thruster data in pound-force seconds, the other read it as newton-seconds. Don't make the same mistake with your reporting as NASA did. Their teams worked from different versions of the truth. Sounds familiar? Reports get manually recreated, adjusted and reconciled before anyone will trust them. Your people spend their time checking and debating the numbers, instead of using them. Book a data scan with All Your BI to decide on one source of truth.

Need to get your service back up and running? Missing data and slow search can delay your investigations and keep your customers waiting. With Bronto, you can store all of your logs, traces, and metrics in full-fidelity for 12 months, retained always hot and instantly searchable. Get reliable answers fast and keep building.

At $0.01 per GB ingested, you can keep all of your logs, traces, and metrics in Bronto for 12 months. Automatically parsed. Instantly searchable. Ready for any query, prompt, or agentic workflow. With all your observability data in one place, you can troubleshoot any error with confidence and surface performance trends over time.

Most Amazon issues ⚠️ show up when sales already slip. CATAPULT Retail Hub highlights early signals across Buy Box, stock, pricing, and traffic so you can easily see what’s changing and why. Want to see how it works? Book a short demo. 🔥 Or request free access and try it for 14 days.

Sales drops on Amazon rarely come from one place. That's why Retail Hub gives you early warning signals across retail KPIs, like Buy Box, stock, traffic or pricing. A single, fully customizable report makes sure you can spot the real cause fast and act with 100% confidence. Want to see how it works? Book a short demo. 🔥 Or request free access and try it for 14 days.

Hear from industry experts and customers, discover how organisations are using data and automation to drive better outcomes, and get the latest updates from the FME ecosystem. Join us in Adelaide or Perth.

The VertiGIS Annual Breakfast Seminar is touring six cities this October. Hear the latest from FME, see where VertiGIS solutions is heading, and hear how organisations like Acciona, Western Power and Decca are putting their spatial data to work.

Most AI attempts stall on real data, not the model. In three weeks we run one real use case on your own past work, measure it, and give you a build, defer or stop for the board.

Copilot, ChatGPT, an agent your team built. Nobody can tell the board how good it is. We measure one use case against your own past wins and losses, inside your own Microsoft 365, in three weeks.

OT and IT still siloed? Every AI use case rebuilds the same integration.

Vous connaissez le rêve : des tableaux de bord en libre-service, moins de tickets, des décisions plus rapides. Vous connaissez aussi la réalité : des tableaux de bord que personne ne consulte, des « enseignements » fondés sur des métriques mal interprétées, et un backlog sans fin de retouches qui deviennent soudain urgentes dès qu'une réunion commence. Pendant ce temps, votre équipe continue de construire, et le métier continue de demander : « Et donc ? » « Dashboard Confessionals » rassemble des citations réelles et anonymes de data leaders et de leurs équipes. Ce qu'on n'avoue qu'une fois l'écran partagé refermé.

Your margin looks healthy at company level, but it is leaking somewhere you cannot see. That is not a data problem, as you already have the operational information. It sits in disconnected views. Operations on one side, finance on the other. So every process gets optimised on its own, and nobody sees what that does to total performance. Book a data scan with All Your BI, and find where your margin is leaking.

More output isn't more impact. Amplitude ADVANTAGE Berlin: Wed 2 Dec, 14:00–19:00 CET, The Delta Campus. Request your spot.

AI isn’t the challenge — your data is. Assess your foundations and unlock scalable, production‑ready AI outcomes.

91% of ISVs say they’re AI‑ready. The data tells a different story. Discover what’s holding teams back and how to fix it.

Most AI architecture diagrams have one small yellow box in the middle. That box is the model, and it gets almost all the attention. In every production AI system I have seen, the hard work sits in the boxes around it: evaluation, guardrails, tool permissions, tracing, cost control, monitoring. That is where pilots either become dependable systems or quietly stall. The numbers show it. McKinsey's State of AI 2026: 44% of organisations say AI is scaling across the enterprise, yet only 37% see any EBIT impact. One in five say running costs already hold them back. Agentics makes this layer even more important. Once AI plans, calls tools and acts on its own, you need to know what it did, what it was allowed to do, and what each completed task cost. That operating discipline is AgentOps. Today we publish paper 1 of our AgentOps Series, written by Partnership Professor @Darius Dilijonas for CTOs and heads of AI, data and platform. In fact it's written for anyone who is interested to learn more about the inner workings of Agent- and MLOps. Three questions from it that I'd put to any leadership team this quarter: → Does every production AI system have a named owner and a budget? → Can you show the cost per completed task for your agents? → Has anyone tested how to stop an agent? If any answer is "not yet", the article is a good place to start. https://lnkd.in/epyn2_Jz For those who want the depth, there is a free download of the full research report on our blog. #AgentOps #Agentics #MLOps #AIinProduction

Time-series data, machine events, JSON, and operational data do not have to live in separate systems. CrateDB brings different data types together in one SQL engine.

Turn production and sensor data into applications your teams can actually use. Build real-time quality analytics without adding another data silo.

We’re #1! 🎉 Axiobench named Import.io Best Overall for Data Extract Software in its 2026 ranking. Thank you to our team and customers! https://lnkd.in/eV4tgdBK

𝗖𝗼𝗺𝗼 𝗮𝘂𝗺𝗲𝗻𝘁𝗮𝗿 𝗮 𝗽𝗿𝗼𝗱𝘂𝘁𝗶𝘃𝗶𝗱𝗮𝗱𝗲 𝗲 𝗿𝗲𝗳𝗼𝗿𝗰̧𝗮𝗿 𝗮 𝗰𝗼𝗺𝗽𝗲𝘁𝗶𝘁𝗶𝘃𝗶𝗱𝗮𝗱𝗲 𝗱𝗮𝘀 𝗲𝗺𝗽𝗿𝗲𝘀𝗮𝘀 𝗽𝗼𝗿𝘁𝘂𝗴𝘂𝗲𝘀𝗮𝘀? Junte-se à Informa D&B e ao Jornal de Negócios para uma manhã de partilha de conhecimento, apresentação de indicadores e debate sobre um dos temas mais relevantes para o crescimento da economia nacional. 🔗 Saiba tudo: https://lnkd.in/e59MbwbY

Combien d'animaux vivent dans votre code postal ? Le Panorama des animaux de compagnie en France permet d'explorer leur présence à l'échelle locale et de comparer les territoires grâce à des données inédites. Collectivités, professionnels du secteur animalier, assureurs, vétérinaires : découvrez les indicateurs clés de votre territoire. Consultez gratuitement l'étude.

Combien d'animaux vivent dans votre code postal ? Le Panorama des animaux de compagnie en France permet d'explorer leur présence à l'échelle locale et de comparer les territoires grâce à des données inédites. Collectivités, professionnels du secteur animalier, assureurs, vétérinaires : découvrez les indicateurs clés de votre territoire. Consultez gratuitement l'étude.