B2B ad examples

Packet data holds the answer to most network questions, but only a few people on your team can read it. With cPacket AI, engineers, app owners, and L1/L2 staff get clear answers without spreading your senior engineers too thin: 💬 Ask questions in plain language 🔍 Follow the same troubleshooting steps as your senior engineers 🚀 Get answers backed by packet evidence Scale expertise across teams without scaling headcount

Your GPUs are portable. Your storage isn't. Multi-vendor GPU stacks have a silent single-vendor dependency: the storage layer. If the compute moves and the data can't follow, the strategy stops at the data. Akave Cloud is S3-compatible and verifiable sovereign storage, so your data stays portable across environments with $0 egress fees. Drop in your current egress bill and see what Zero egress bill looks like against it.

If your GPUs are portable across vendors and your storage is not, You are locked in wherever the storage lives. The multi-vendor GPU pattern has a silent single-vendor dependency: The storage layer. Akave Cloud provides S3 compatible, verifiable storage layer which reduces single vendor dependency and makes your data portable with $0 egress fees. Don't believe us? Try Akave Cloud Risk free or compare the egress cost to compare how much you save with us?

Ellipsis Drive catalogs spatial data across existing storage, helping teams and applications find and use it without moving source files.

🗺️ 𝗥𝗮𝘀𝘁𝗲𝗿 𝗱𝗮𝘁𝗮 𝗶𝘀 𝗮 𝗴𝗼𝗼𝗱 𝗲𝘅𝗮𝗺𝗽𝗹𝗲 𝗼𝗳 𝘄𝗵𝘆 𝗼𝗻𝗲 𝘀𝘁𝗼𝗿𝗮𝗴𝗲 𝗮𝗯𝘀𝘁𝗿𝗮𝗰𝘁𝗶𝗼𝗻 𝗱𝗼𝗲𝘀𝗻'𝘁 𝗻𝗲𝗰𝗲𝘀𝘀𝗮𝗿𝗶𝗹𝘆 𝗳𝗶𝘁 𝗮𝗹𝗹 𝗱𝗮𝘁𝗮. Its spatial relationships are fundamental to how it needs to be stored, accessed and processed, something a tabular abstraction doesn't naturally preserve. The result? More complexity gets pushed downstream onto the data team.

Simplify EDI & reduce costs: Automate orders with accuracy across retail, pharma, marketplaces, 3PLs, and more. 1,500 partners and full ERP integration. Free up teams for more.

Keep orders moving and opportunities growing with full-scope EDI compliance and modern order management. Order automation meets clean data insights.

A private field service executive community with zero vendors in it. No vendors trying to sell you. No junior marketers. No upsells. Only your peers in field service.

A private field service executive community with zero vendors in it. No vendors trying to sell you. No junior marketers. No upsells. Only your peers in field service.

When latency spikes, decisions miss their window. In an independent benchmark against Redis, Aerospike matched in-memory latency with far less jitter, even when serving data straight from disk. See the results across four configurations.

Ihr Mitbewerb nutzt wahrscheinlich dieselbe KI wie Sie. 🤖 Den Unterschied macht jedoch nicht das Modell - sondern Ihre Datenqualität. In unserer kostenlosen 5-teiligen Webinar-Reihe zeigt Tobias Pentek, AI-Experte bei CDQ, warum vertrauenswürdige Daten der wahre Wettbewerbsvorteil im KI-Zeitalter sind. 📅 Start: 6. Oktober 2026, live dienstags, 15:00 Uhr ✅ Kostenlos · 5 Folgen 🎥 Aufzeichnung automatisch per E-Mail 🎁 Bonus: CDQ Genius live in Folge 5 Einmal anmelden, Zugang zu allen 5 Folgen.

Your AI model probably isn't the problem. Your data might be. 🎯 Duplicate records, missing fields, unverified suppliers quietly undermine every AI initiative built on top of them. Find out where your data actually stands with CDQ's free AI Readiness Scorecard. ✅ Free · takes minutes 📊 Score 0–100 across 5 weighted dimensions 🔍 See exactly where the gaps are, not just that they exist 🗺️ Get a clear next step, not just a report card

Scaling great brands globally takes more than great products. Here's how multi-brand consumer goods businesses are turning AI into a group-wide operational advantage. Swipe through to see how BizData helps consumer goods businesses embed AI consistently across product, merchandising, and operational workflows — transforming brand-level experiments into a compound group capability.

Misclassified inventory eating into your CPMs? Need to add device identification to your existing bid-request flow without a rebuild? Your in-house parser can't keep up with the CTV device long tail? Whatever your challenge, bring it to Stand B059a. We'll be at DMEXCO 2026, Hall 06.1, September 23–24 — ready to work through it with you in person. #DMEXCO2026 #CTV #AdTech #Programmatic *Source: DeviceAtlas

🚀 Bis zu 30.000 € Förderung für den Einstieg in Catena-X Steigende Anforderungen ihrer Kunden, neue Berichtspflichten und fragile Lieferketten stellen viele Unternehmen der Automobilindustrie vor dieselbe Aufgabe: Informationen müssen schnell, sicher und effizient mit Partnern ausgetauscht werden. Das geht mit Catena-X: Der Datenraum ermöglicht Unternehmen, Daten nach gemeinsamen Standards und Regeln über einheitliche Prozesse mit ihren Geschäftspartnern auszutauschen. Das Wichtigste: Sie behalten die Kontrolle und entscheiden, welche Informationen Sie mit welchen Partnern teilen. Die Daten werden weder in einer geteilten Plattform gesammelt noch zentral verwaltet. Typische Anwendungen sind der Austausch von CO₂-Daten, Qualitätsinformationen oder Angaben zu verfügbaren Kapazitäten und Bedarfen. Der Einstieg ist 2026 so leicht wie noch nie: Im Rahmen einer Studie der deutschen Bundesregierung erhalten Unternehmen finanzielle Unterstützung, um einen produktiven Datenaustausch in Catena-X aufzubauen. Je nach Anwendungsfall stehen 15.000 € oder 30.000 € Fördermittel zur Verfügung, um die anfänglichen Implementierungs- und Einstiegskosten abzudecken. Besonders interessant ist das Angebot für: ✅ KMU und Unternehmen, die Catena-X erstmals nutzen möchten ✅ Organisationen mit wenig Erfahrung im Bereich Data Spaces ✅ Teams, die konkrete Anwendungsfälle umsetzen wollen, z. B. Product Carbon Footprint (PCF), Zertifikatsmanagement oder den Digitalen Batteriepass 🏛️ Der Data Space Accelerator wird durch das Bundesministerium für Wirtschaft und Energie gefördert und verfügt über ein Fördervolumen von 23 Millionen Euro. Die Studie läuft ausschließlich im Jahr 2026. Interessiert? 🔗 Mehr erfahren und bewerben: https://lnkd.in/exaXSX-a

Up to €30,000 in funding to get started with Catena-X 🚘 Automakers are increasingly requiring their upstream partners to participate in Catena-X. For some OEMs, data exchange on Catena-X is even already a requirement in their tender conditions. In particular, the exchange of company certificates and Product Carbon Footprints (PCF) is increasingly being required. In 2026, a government-funded study will support companies in getting started: 💶 €15,000 in funding for Company Certificate Management (CCM) or €30,000 for CCM and PCF ✅ Support with initial setup and implementation costs ✅ Particularly interesting for companies looking to implement their first Catena-X use cases 🏛️ The Data Space Accelerator is funded by the Federal Ministry for Economic Affairs and Energy and has a total funding volume of 23 million euros. This funding is available exclusively in 2026. If you’re planning to get started with Catena-X, now is a good time to take the next step. 🔗 Learn more and apply: https://lnkd.in/eRz6K2rv

Crescer sem qualificar dados não transforma volume em escala. Transforma volume em risco. Para instituições de pagamento, gateways e subadquirentes, cada novo cadastro, transação e relação comercial exige informações consistentes e confiáveis. Sem uma validação adequada, o crescimento da operação também pode aumentar: • Tentativas de fraude • Decisões baseadas em dados incompletos • Retrabalho operacional • Exposição regulatória A DataHub apoia o ecossistema de pagamentos com soluções de validação cadastral, análise de risco e enriquecimento de dados. Conheça melhor quem entra na sua base e aumente a segurança das suas operações.

Sua empresa sabe quem está por trás de cada cadastro? Informações incompletas dificultam a identificação de riscos e podem expor sua operação a fraudes. Com a Datahub, sua equipe conta com inteligência de dados para analisar perfis e comportamentos, fortalecer o KYC e apoiar as rotinas de compliance. Conheça melhor seus clientes e tenha mais informação para decidir com segurança. Clique em Saiba mais e descubra como a Datahub pode apoiar sua operação.

Today we're introducing Cockroach Continuum, built for an era when agentic applications are growing database estates faster than any team can manage by hand. Bring a workload, and Cockroach Continuum folds it into the shared estate — pooling capacity across thousands of isolated databases instead of provisioning each one for its own peak. Cockroach Plenum, our usage-based storage layer, means you pay for the storage workloads actually use rather than what gets provisioned. Cockroach Aegis, a system of agents, watches the estate continuously, observing, recommending, and, under your governance, acting with growing autonomy over time. The foundation is CockroachDB, the same engine trusted in production for a decade. Cockroach Continuum is what it evolves into next. 🪳 Alongside Cockroach Continuum, we're unveiling a new look. A visual identity built on the same principles as the product: resilience, adaptability, and technology designed to stay up for anything. https://lnkd.in/eAWijr2q

🏃➡️ Vi løber hurtigt, så du ikke behøver at gøre det! 🏃♀️ Vi har flest direkte telefonnumre af alle udbydere ☎️ 👉 OG vi har samlet al den information, du kunne få brug for til B2B og B2C. 👉 OG det hele opdateres uden du skal røre en finger. 👉 OG du får adgang til det via vores portal eller direkte i jeres systemer. 👉 OG så får du en direkte linje til Danmarks bedste dataspecialister! Med god data løber du altid i den rigtige retning – uden at snuble. datapeeps.dk

Dashboards are unfortunate creatures. Nobody wants them to be what they are. Executives wish they were self-updating slide decks. Instead of charts in a boring grid, they wish for dazzling visuals, a big header, one metric per tab, while still seeing the applied filters and changing them on the fly. Marketing wishes it were a story. Instead of rows of numbers, they wish for a narrative so convincing that everyone nods along to whatever wild idea comes next, and agrees that the metrics colored in red are probably the market's fault. Revenue wishes it were a crystal ball, handing out predictions and projections built on historical CPL, CAC, and whatever else it can get its hands on. They all wish the dashboard could be more. But most of the time a dashboard is the place to look at, not the place to act on. Now it can be more. Our new HTML Layout frees you from the fixed canvas. You can just use HTML and CSS to build highly tailored data experiences - storytelling slides, print-perfect reports, or even data game. This update also makes Holistics much more vibe-coding-friendly: the output is now plain HTML, a language AI already writes fluently, rather than a proprietary layout format. Soon you'll be able to just describe the data experience you want and Holistics AI will build it for you.

"I find your AI to be surprisingly accurate". A customer told us this a while back, and it's a compliment we've had mixed feelings about ever since. The "accurate" part we're glad to hear. An AI chatbot that isn't accurate doesn't have much reason to exist. That’s its entire job. But why the surprise? Is it because the gap between what data vendors promise and what they actually deliver has grown to the size of a sinkhole - big enough that an AI simply not making things up now counts as a pleasant surprise rather than the baseline? Or is it that we haven't done a good enough job marketing our AI? The former is collectively an industry problem, and not much we can do about it on our own. The latter, though, we can control. So here's something you might not know our AI can do: EVERYTHING, actually. In this 3-minute video, our product manager shows how he used our latest feature, Local Agentic Development, which lets you bring the coding agents you already know - in this case, Claude Code - and pair them with Holistics through MCP to go from raw schema to a fully functional, well-governed dashboard in just a few minutes. Have a look. And if you already use Holistics, give it a try.

A valid login proves who’s requesting data – not what it should access. The Data Authorization Layer makes that decision.

Trace #sampling allows you to harness the power of distributed tracing without breaking the bank, but also adds inaccuracies; let's talk about how you fix that. There are two commonplace ways of doing sampling: probabilistic #HeadSampling and #TailSampling. With probabilistic head sampling, it is like you throw a die for every trace, and keep the trace only if the die's face is low enough. With tail sampling, you collect the traces and keep those that are *interesting*, typically slow ones and erroneous ones. Head and tail sampling reduce the accuracy of your data, over or underestimating error rates and latencies of your services. (Btw, creating animations with LLMs is pretty addictive.) What can you do to reduce inaccuracies? You additionally record rate, errors and durations (RED) metrics for your services on the full data before sampling. With #OpenTelemetry, you can do trace sampling and #RED metrics collection with the same pipeline setup. Sometimes you also combine the two methods: tail sampling for interesting traces and probabilistic head sampling for baselines. However, processing the resulting data in alerting and dashboards is usually a challenge, while RED metrics make it easy. I wrote an article about this a little while ago that is still pretty relevant, and there is also an accompanying talk, which I fearlessly link in the main post: * https://lnkd.in/eKJCyuXy * https://lnkd.in/eRaczB4N What else do you do to improve the accuracy of trace sampling?