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Veel KMO-leiders schrikken terug voor BI omdat het klinkt als een IT-project van een jaar. Bij Dicar was de zoektocht hetzelfde. "We wilden vermijden dat we in complexiteit zouden belanden. Het moest begrijpbaar blijven voor iedereen." Met InsightData kreeg Dicar geen developer-afhankelijke tool, maar een BI-omgeving die finance, sales, operations en supply chain begrijpt. Elke app live in 8 weken. Geen IT-traject van meer dan een jaar. Lees de Dicar case study en zie hoe zij dat aanpakten. #BeslistBeter #BusinessIntelligence #PlugAndPlay #KMO

You do not need to trade Spark compatibility for infrastructure control. IOMETE gives data teams the Spark, SQL and notebook workflows they know—on infrastructure they control. Customers save 2–5x over cloud-only platforms. See the cost model →

Messi data? Not our game. We keep score, so you never lose sight of what's happening on the field. https://lnkd.in/dT3QPvPJ

Your proxy provider got blocked❓ Infatica.io gives you a path forward. Our enterprise-grade proxy and web data platform is built on verifiable, ethical sourcing with revocable, opt-in peer participation, strong KYC, and abuse prevention. You still get global coverage, 99.9% uptime, and flexible HTTP(S)/SOCKS5 access, without compromising compliance.

Ever feel that chill when your proxy provider suddenly gets blocked? With Infatica.io, you trade panic for peace of mind: you get an enterprise-grade proxy and web data platform built on verifiable, ethical sourcing, revocable opt-in peers, strong KYC, and real abuse prevention, so your conscience and your compliance team can both relax while you keep global coverage, 99.9% uptime, and flexible HTTP(S)/SOCKS5 access humming along.

Want to start your day with a clear overview of observed price, promotion and listing changes across retailers? IPV Data gives you a daily update before 8am on observed price, promotion and listing changes from the past 24 hours: • Product-level changes • Price changes from the past 24 hours • Direct links to the detailed product view • Filter options by retailer or category Stay informed about the latest observed market changes across retailers. Book your demo → https://lnkd.in/eeDvFe-T

Seniors isolés, professions libérales, zones rurales : ces profils existent dans vos cibles, mais rarement dans vos bases de données. 🧐 Résultat : des relances multipliées, des délais qui s'allongent, et des pondérations statistiques de plus en plus lourdes pour compenser ce qui n'a pas été capté en amont. Pas besoin de relancer davantage. Juste des bases enrichies, pour cibler ces profils directement. Ce livre blanc vous montre comment toucher les populations difficiles à atteindre. Téléchargez-le maintenant.

Un quota respecté n'est pas toujours un panel représentatif. Vos indicateurs globaux sont au vert. Mais un biais peut se cacher dans le détail (une CSP, une zone géographique, une tranche d'âge) sans que vous le voyiez 👀 Pas besoin d'interroger plus de monde. Juste les bons profils, dès la construction de l'échantillon. Nous avons accompagné plusieurs instituts de sondage dans la sécurisation de leurs quotas, sans complexifier leur méthodologie terrain. Et si c'était à votre tour ? Cette checklist détaille les 9 critères pour construire un échantillon réellement représentatif. Téléchargez la checklist maintenant

𝐘𝐨𝐮𝐫 𝐂𝐚𝐬𝐬𝐚𝐧𝐝𝐫𝐚® 𝐰𝐨𝐫𝐤𝐥𝐨𝐚𝐝𝐬 𝐝𝐞𝐬𝐞𝐫𝐯𝐞 𝐢𝐧𝐟𝐫𝐚𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞 𝐛𝐮𝐢𝐥𝐭 𝐭𝐨 𝐤𝐞𝐞𝐩 𝐮𝐩. With NetApp Instaclustr, get the 𝐩𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞, 𝐫𝐞𝐬𝐢𝐥𝐢𝐞𝐧𝐜𝐞, 𝐬𝐞𝐜𝐮𝐫𝐢𝐭𝐲, and 𝐬𝐜𝐚𝐥𝐚𝐛𝐢𝐥𝐢𝐭𝐲 your critical workloads demand—without the operational complexity. Our experts manage your Cassandra® environment at every stage, so your teams can focus on building and innovating instead of managing infrastructure.

Finding Cassandra® complex to manage at scale? Talk to experts who work with Cassandra every day to 𝐬𝐢𝐦𝐩𝐥𝐢𝐟𝐲 𝐨𝐩𝐞𝐫𝐚𝐭𝐢𝐨𝐧𝐬, 𝐨𝐩𝐭𝐢𝐦𝐢𝐳𝐞 𝐩𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞, 𝐚𝐧𝐝 𝐤𝐞𝐞𝐩 𝐜𝐫𝐢𝐭𝐢𝐜𝐚𝐥 𝐰𝐨𝐫𝐤𝐥𝐨𝐚𝐝𝐬 𝐫𝐮𝐧𝐧𝐢𝐧𝐠 at their best.

One-off AI projects are a liability. Tobias Zwingmann explains why teams building roadmaps, not projects, generate consistent ROI in his InterSystems READY 2026 Keynote.

Three things stand between you and profitable AI: metrics, thresholds & a roadmap. Tobias Zwingmann breaks down how to build them in his InterSystems READY 2026 Keyonote.

Educação transforma vidas! A Informa D&B acaba de lançar a 2ª edição do Programa INFORMA EDUCA 2026, que apoia projetos educativos de instituições sem fins lucrativos. Representa ou conhece uma instituição com este propósito? Partilhe e/ou candidate-se!

When the stakes are highest, you need complete visibility. Get real-time analytics at global scale and deliver high-quality experiences during the biggest events of the year.

Teams keep telling me their AI projects aren't delivering, so we go and look at the model. The model is almost never where it breaks (exceptions aside). It's usually underneath, in the data foundation everyone assumed was fine, or that got blatantly ignored under the pressure to ship. Hidden technical debt rarely announces itself, causing silent data dependencies with pipelines that got tangled over years of "we'll clean it up later." Or things like a metric that quietly means something different for different departments in different countries they operate in. None of this shows up as a crisis. Rather it shows up as friction, with reports taking longer and business processes that quietly stop behaving the way they used to. Confidence in the numbers erodes a little at a time. Every new use case costs more than the last, because they're building on things nobody wants to touch. Then someone suggested to put AI on top, and AI doesn't forgive ambiguity the way a human analyst does. It scales whatever is underneath it, including the mess. Getting themselves stuck... Sorting it out is mostly unglamorous and unpopular work. It takes clear ownership of data, definitions that hold across business units and markets, pipelines you can change without holding your breath, and a AI-ready data stack solid enough to cope with the supercharger you're strapping on top. With governance built in from the start rather than bolted on later makes a huge difference. All of that is slower than building a demo, of course, but it's the version that survives contact with production. We wrote a more in-depth piece on what this technical debt looks like up close, why it compounds. Worth the read if you're scaling on a stack you're not fully sure of: https://lnkd.in/eFJ3eGNX And if any of this feels familiar, DM me or reach out to the team at https://lnkd.in/e39cCm8e. Happy to talk it through.

Externa faktorer pressar ekonomiavdelningarna allt hårdare – men hur förberedda är de egentligen? 489 CFO:er svarar i Confessions of a Nordic CFO 2026. Förbeställ redan idag.

489 CFO:er och ekonomichefer i Norden delar med sig av sin vardag. Svaren avslöjar ett gap mellan känsla och verklighet. Förbeställ Confessions of a Nordic CFO 2026 – släpps i september.

You look at traffic every day, but do you actually know what is real? Bots, noise, and inflated signals can skew everything from performance to decision making. Run your traffic through Hydrolix and see what is actually happening.

This week we published yet another article that goes deeper into the challenges of building Enterprise grade AI and the Data stacks that need to support it. Excuse the cheesy AI generated illustration, but someone in my team thought it was nice... We found that most organisations still treat AI like 'software'. They evaluate it, buy it, switch it on, expect it working by Friday. That mental model is where the trouble starts. Someone provided us with a very nice 'garden' analogy in one of our earlier articles, which we are keen on borrowing. You see, AI behaves less like a product you install and more like a crop you grow. It draws everything it needs from the ground beneath it. If that ground is thin or compacted, nothing you plant on top will grow, no matter how good the seed (at least not in the long run). And by today's standard, the seed is rarely the problem. Capable models are abundant and often free to start with. The reason so many AI initiatives stall in the same place, somewhere between an impressive pilot and anything that runs in daily operations, is that the ground was never prepared. Our latest piece looks forward, at the foundation worth building on purpose: why a warehouse is not a platform, what governance actually speeds up, and why roughly half of an AI-ready platform is not technology at all. If there is one lesson to take with you: AI tools are not magic, and outcomes are engineered. A capable model on a weak foundation produces fragile results that never earn the trust required to run a business. A modern, governed, well-owned data platform produces the opposite, and it keeps producing long after any single project ends. The most useful question isn't whether the models are good enough. They almost certainly are. It's whether the ground beneath them is ready. Read the full article below. https://lnkd.in/eqZYEwND

Power BI už máte. Přesto váš finanční tým každý měsíc ručně připravuje data, kontroluje verze a opravuje chyby? Reporting pak funguje, ale stojí zbytečně moc času. V intecs propojujeme reporting, plánování, forecast a automatizaci nad jedním datovým základem. Finance tak mají rychleji k dispozici čísla, kterým mohou věřit, a víc času na jejich analýzu. Podívejte se, jak může moderní finanční reporting fungovat: https://lnkd.in/eS_YQiPP Pokud už podobné téma řešíte a chcete ho rovnou probrat, domluvte si nezávaznou konzultaci: https://lnkd.in/e82uMJPU

🔏 Las organizaciones ya están incorporando nuevas capacidades para proteger los datos, automatizar operaciones de privacidad y responder a los riesgos que trae la IA. ¿La pregunta? Qué tecnologías priorizar y por dónde empezar. Descubre qué está entrando en el radar de CIOs, CISOs y DPOs en el Gartner® Hype Cycle™ for Privacy, 2026. ✅ Consulta el informe y acelera tu estrategia de privacidad.

El Gartner® Hype Cycle™ for Privacy, 2026 analiza las principales tecnologías y capacidades de privacidad, su nivel de madurez, el tiempo estimado hasta su adopción generalizada y su potencial de impacto, ayudando a los equipos a entender qué priorizar y dónde poner el foco. ✅ Descarga el informe.

Your client paid expert rates. The expert typed the question into ChatGPT and read the answer back. We check every call for it and tell you if your experts are risking your credibility. Runs on the transcription pipeline you already use. Get an AI plagiarism audit of your own calls.

Your client paid expert rates. The expert typed the question into ChatGPT and read the answer back. We check every call for it and tell you if your experts are risking your credibility. Runs on the transcription pipeline you already use. Get an AI plagiarism audit of your own calls.