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Access all of your observability data for 12 month. Short retention windows lead to blind spots, but teams are forced to accept it to keep costs down. With Bronto, all of your data is retained for 12 months by default. No extra costs or rehydration – just all of your data instantly searchable.

Investigations rely on evidence. If you're sampling down your observability data, you could be throwing away important clues. If your logs are only searchable for a few days, you lose visibility into performance trends over time or recurring issues. With Bronto, you can keep all of your logs, traces, and metrics in full-fidelity for 12 months, retained always hot and instantly searchable. Solve every case with confidence.

Only optimizing the top 10% of your Amazon listings? ⚠️You’re likely losing revenue — every month (without even realizing it). Reason? Unoptimized ASINs drag down your visibility, conversions, and ROI across your entire catalog. Now your team can manage the other 90%, and do it 80% faster! 👉 Meet Amazon Portfolio Management: AI, powerful reporting & dedicated support in one.

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 Breakfast Seminar is an educational morning. Hear real-world customer success stories, see VertiGIS solutions in action, gain insights into emerging industry trends, and connect with peers through valuable networking and knowledge-sharing opportunities. Adelaide 27 October and Perth 28 October.

Your AI strategy is only as strong as your data foundation. Assess gaps, strengthen governance, and unlock scalable enterprise AI.

AI investment is booming. Enterprise expectations are outpacing delivery. See what 300 ISVs are doing to close the gap.

High-speed filling creates high-volume data. Turn that data into real-time production insight and identify issues before they impact the line.

Bring uptime, downtime, production events, and sensor readings together for real-time production analytics. Build faster insights on a single SQL data layer.

What should an agent do at a venture fund, and what should stay with the investor? Max Ruderman, Keshvi Radia, Dr. Andre Retterath and Yohei Nakajima have opinions. Save your spot: https://luma.com/0b5yswul

I just pulled every long-tenured OpenAI engineer (name, title, start date and LinkedIn). This is where the startup mafias come from. Two reasons why: 1) I imagine that most of these engineers will leave soon to go back to 0 to 1 building 2) They are likely fully vested so they do not have to stay at OpenAI to receive their huge payouts I got the below list using Harmonic’s research tool. I then put this into an active list so that I could get more enriched data on each person that updates automatically (it updates once a week with new details from Linkedin). This info is tablestakes in today's venture game. In case you want to check it out yourself: www.harmonic.ai/try cc: Harmonic #harmonicpartner #venturecapital #sourcing #startup

Votre code postal est-il au-dessus ou en dessous de la moyenne ? Le Panorama des animaux de compagnie en France révèle des écarts parfois surprenants entre territoires. Découvrez combien d'animaux vivent dans votre zone géographique et comparez-la aux autres territoires. La réponse est dans l'étude.

Votre code postal est-il au-dessus ou en dessous de la moyenne ? Le Panorama des animaux de compagnie en France révèle des écarts parfois surprenants entre territoires. Découvrez combien d'animaux vivent dans votre zone géographique et comparez-la aux autres territoires. La réponse est dans l'étude.

Is manual data reconciliation slowing down your insurance operations? Property & Casualty (P&C) insurers rely on accurate, consistent data across financial systems, production environments, and business applications. But as data ecosystems grow, validating information across hundreds of interfaces and pipelines can become complex, time-consuming, and resource-intensive. For one U.S. property insurer, managing 600–800 data interfaces and pipelines created a significant need to streamline financial and production data reconciliation. The solution? Automated data validation and reconciliation with Datagaps. By automating key testing and reconciliation workflows, the insurer achieved measurable improvements: ✅ 90% reduction in test execution time — accelerate validation cycles and reduce manual effort. ✅ 2X expansion in line-of-business coverage — extend testing coverage across more business areas. ✅ 50% reduction in testing team size — optimize resources while supporting broader testing needs. These results demonstrate how automation can help insurers modernize data quality processes, improve operational efficiency, and build greater confidence in business-critical data. Could your insurance organization benefit from automated data reconciliation? Discover how datagaps helped this U.S. property insurer streamline financial and production data reconciliation—and explore what a similar approach could mean for your organization.

Discover how brand lift measurement can connect campaign exposure to changes in awareness, favorability, and purchase intent, even across walled gardens.

Awareness, familiarity, consideration, favorability and purchase intent, measured consistently across social, CTV, audio and offline. See how it works.

This fall, we’re on the road: 𝗖𝗵𝗶𝗰𝗮𝗴𝗼 → 𝗦𝗮𝗻 𝗙𝗿𝗮𝗻𝗰𝗶𝘀𝗰𝗼 → 𝗟𝗼𝗻𝗱𝗼𝗻 → 𝗡𝗲𝘄 𝗬𝗼𝗿𝗸. ⠀ A packed few weeks with live demos, Spark & Spirits happy hours, and deep technical conversations. ⠀ I’ll also be on stage in London and NYC, talking about 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗖𝗼𝘀𝘁 𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻 𝗳𝗼𝗿 𝗦𝗽𝗮𝗿𝗸 𝗮𝗻𝗱 𝗗𝗮𝘁𝗮𝗯𝗿𝗶𝗰𝗸𝘀. ⠀ One of my favorite parts of the job – connecting in person with the Databricks and Data Engineer Things communities. ⠀ 𝗕𝗿𝗶𝗻𝗴 𝘂𝘀 𝘆𝗼𝘂𝗿 𝘁𝗼𝘂𝗴𝗵𝗲𝘀𝘁 𝗽𝗶𝗽𝗲𝗹𝗶𝗻𝗲. 𝗪𝗲’𝗹𝗹 𝗼𝗽𝘁𝗶𝗺𝗶𝘇𝗲 𝗶𝘁.

When the network drops, your business shouldn't stop. Couchbase keeps field and mobile apps running with continuous data sync from cloud to edge to device. See how.

Introducing 3D Zones, now available in Cognitive3D. 3D Zones gives XR and robotics teams a new way to measure activity within the areas that matter to their applications. Draw and name Zones directly on your 3D scene, then track visits, time spent, and activity based on position, gaze, or line of sight. You can also explore historical data within an area, compare Zone behaviour across sessions, and use location and duration as part of pass/fail Objectives. By turning meaningful areas into measurable data, 3D Zones adds another layer of spatial context to the sessions you already capture with Cognitive3D. 3D Zones is generally available now and appears as Zones in the Cognitive3D dashboard. Learn more and see it in action: https://lnkd.in/g4ZiDXZp

Stop stitching together five systems behind one mobile app. Couchbase delivers on-device vector search and edge AI that work in dead zones.

See how NetOps NCM auto-remediation from Broadcom helps reduce MTTR.

See how to eliminate manual configuration errors using automation, in this NetOps NCM walkthrough.

Will AI end up destroying humanity? I don't know, and I doubt anyone else does either. What I do know for certain is AI will destroy valuable data along the way. Database applications have built-in gates to reduce the chance of accidental deletion. The big danger is database administration. At Altinity, Inc. we have seen multiple cases where customer AI agents with admin credentials erased production data. The people running the agents were employees, not attackers. As Pogo said, "we have met the enemy and he is us." Solving the problem is going to be hard. Database administration commonly involves manual procedures and custom scripts--lots of both, often with very high privileges. The working assumption is that very paranoid humans carry these out. That's no longer true when AI agents enter the house. The quick solution is simple: don't use agents for database administration. That includes using ChatGPT and Claude to generate procedures. Of course people will do so anyway, because it's convenient. The fallback is to test the living daylights out of anything you get from an AI agent. Make sure your backups are good, too. The longer solution? For that we need to understand how AI is changing database administration, then start to build in protections systematically. Some of the possibilities include new database security checks, AI watchdog agents, and baking human oversight into the loop. We'll figure it out and the result will be better administration of data. But it will take time. Losing production data is horrible. I did it on a grand scale in my first IT job thanks to a mistake in running backups. So I have some simple advice if you are adding agent-based administration on data you value. Follow the advice of the old Eagle song: "take it easy." And stay paranoid. Paranoia never goes out of style when you manage data. p.s., The image was generated by ChatGPT. It does a good job, but I don't let it anywhere near data. #opensource #databases #ai #chatgpt #claude #disasterrecovery #agentic

쌓여 있는 콘텐츠와 산업 데이터, 연구 자료가 AI 학습용으로 거래될 수 있습니다. RDPGROUP이 보유 데이터의 시장가격을 진단하고, 판매와 수요처 연결까지 함께합니다. 저작권은 그대로 귀사에 있습니다. 지금 데이터 시장가격 진단을 신청해 보세요.