B2B ad examples

Find out how leading teams are future-proofing their infrastructure before AI demands overwhelm it.

Modernize now or spend the next year firefighting scale, reliability, and cost issues.

Every Solvency II reporting cycle, your team gets pulled off the roadmap to rebuild documentation and reconcile sources by hand for the QRT and SFCR. Same scramble, every quarter. DataGalaxy keeps that documentation current automatically, so each cycle starts with the evidence already in place and your people stay on the work that moves the data org forward.

Mapping Europe and Israel's startups mafias: the 2026 Founders Factory report is now live! Produced in partnership with Accel, with data from Dealroom and Revelio Labs. Europe and Israel's startup ecosystem flywheel is spinning. Employees from 322 VC-backed unicorns have gone on to found more than 2,300 startups across the region, raising over $42B and creating a self-sustaining ecosystem where talent, experience and capital compound with each generation of founders. At the same time, AI is accelerating this momentum, creating a new generation of companies that are scaling from zero to unicorn status in record time. Read the full report below 👇

Bring file, object, cloud and tape together under one intelligent namespace with a simple 4U appliance that fits your existing environment.

Your storage doesn't need replacing. Harmony Data Bridge unifies file, object, cloud and tape into one namespace—without disruption.

𝗖𝗵𝗼𝗼𝘀𝗶𝗻𝗴 𝘁𝗵𝗲 𝘄𝗿𝗼𝗻𝗴 𝗱𝗮𝘁𝗮 𝗰𝗮𝘁𝗮𝗹𝗼𝗴 𝘄𝗶𝗹𝗹 𝗰𝗼𝘀𝘁 𝘆𝗼𝘂. Don’t get locked into hidden fees, clunky interfaces, or a tool that doesn’t scale. We’ve benchmarked 12 leading solutions side-by-side — including Atlan, Collibra, Informatica, Purview, and more — so you can find the one that fits your goals, team, and stack. Inside the 2026 Comparison Guide: - Feature-by-feature product grid - Pricing factors (and hidden costs) - Vendor strengths & weaknesses - G2 Grid analysis ⬇️ Download the free guide and make your shortlist with confidence.

Built for the most regulated industries in Europe. Dawiso shows teams where sensitive data lives and who can access it, with automated PII tracking that follows your data downstream. Read the full guide 👇

📢 Vores undersøgelser viser, at folk i langt højere grad vil arbejde i stedet for at holde fri... For hvis man har god data, så arbejder det altså for én - og ikke omvendt. Men det bestemmer man jo heldigvis selv 😅

📽️ DataPeeps startede med idéen om, at selv små budgetter skal kunne give adgang til gode data. Før i tiden skulle man være en kæmpestor virksomhed med millionbudgetter og et dedikeret data-team, der kunne sidde og indhente og ajourføre data. Dén tid er heldigvis forbi! 😮💨 For du skal ikke gøre forskel på det, Jonas!

The work researchers on deserves to travel: into briefings, classrooms, newsrooms, and the public mind. We make that happen, and we do it without ever distorting what the data says. At Darkhorse Visualization, we help carry your research the last mile and ensure it resonates with policymakers and the public.

Your compliance team said no to dbt Cloud. For enterprise data teams in regulated industries - pharma, healthcare, financial services - SaaS deployment isn't a preference issue. It's a hard blocker. Datacoves deploys managed dbt Core and Airflow entirely inside your own AWS or Azure account. Your firewall. Your security policies. Your data never touches our infrastructure. Production-ready in 3 weeks. Organizations like J&J run Datacoves inside their private cloud today.

Anthropic automates 95% of their internal business analytics with Claude, at around 95% accuracy. The number that matters more is buried in the writeup. Strip out the skills and reference docs they built on top of their data, and accuracy dropped to 21%. Same model. Same warehouse. The difference was the work to establish a solid foundation. Their team even tried handing the agent thousands of prior queries, every question already answered correctly. Accuracy barely moved. The right answer was usually right there. The agent read it and still got the question wrong. The bottleneck was structure, whether "revenue for product X" resolves to one governed table or forty. This is what we've told Datacoves customers since day one. A solid foundation matters. If something is simple for a human, it will also be simple for AI. Ownership, modeling, testing, documentation, automated governance, none of this changes. AI doesn't make that boring work optional, It raises the cost of skipping it. The friction I see constantly: teams chase a quick win, pick dbt + Snowflake, point an LLM at the warehouse, ship the demo that looks like magic. The dream lasts right up until someone forwards a confidently wrong number. Do the foundation work first. Everything downstream gets simpler and more accurate. I've linked posts in the comments where we've been making this case for years.

Messy UTM’s mean messy data, and wasted ad spend. The UTM Playbook helps Marketers build a clean, reliable tagging system, avoid the most common mistakes, and generate perfect UTMs in seconds with our free tool. Track every campaign with confidence and turn messy marketing into clear insights.

Facebook says it’s driving conversions. Google says the same. And TikTok? They’re claiming credit too. Without proper UTMs, it’s impossible to know which platform is actually driving results. The UTM Playbook gives marketers a clear framework for tagging, outlines common pitfalls to avoid, and includes free access to Daasity’s UTM Generator so you can finally see where your leads really come from.

Pension and Growth Capital in Europe 🇪🇺 Europe's VC-backed ecosystem has grown to $4.3 trillion, yet only about 0.1% of the region's $15 trillion pension and insurance pool has ever reached venture capital. New analysis from dealroom.co presented at TechBBQ European Growth Pension and Insurance Summit, Copenhagen.

One thing John hates about being Operations Director is that Finance, Projects, and Site all have their IT systems. But – somehow! – John’s spreadsheet is the only place where the whole company comes together. He calls it “the master”; he prays nobody breaks it; he knows deep inside this is not OK. Is there a quick solution? Read more to find out.

Every quarter another team buys a bigger instance instead of fixing the queries underneath it. The indexes, N+1 queries and over provisioning inflating your Postgres bill are usually fixable. Get a free review with our team to find and fix them today!

Outages are fixable. Lost customer trust isn't. DBGorilla catches the issues before they reach production, so you never have to explain anything to anyone. Get your free assessment.

Our Customer Success team is growing. So we're looking for another teammate who's ready to jump in and help! We're looking for someone who'll make this journey their own. From the first onboarding, through adoption, all the way to the moment a customer calls you because they want to get more out of Dawiso. Ready for a place where you can finally move forward and grow? Get in touch! 📍 Prague, Karlín / Hybrid

Tellum — automation & integration for contractors. Join up your IT systems for clarity of operations.

Was fehlt Ihrer KI, wenn Jahrzehnte Unternehmenswissen in SAP-Systemen stecken? Nicht unbedingt ein besseres Modell. Sondern Zugriff auf die richtigen Daten – inklusive ihres Business-Kontexts. Bei DEUTZ werden historische SAP-Informationen mit ihren Zusammenhängen bewahrt und in die OttoVerse-Umgebung eingebunden. Erleben Sie bei DSAG, wie Enterprise Data für die AI-Ära nutzbar wird. 📍 6. Oktober · Köln · Stand D15

Was weiß Ihre KI über Ihr Unternehmen? Das Modell ist nur ein Teil der Gleichung. Entscheidend sind Unternehmensdaten – zugänglich, nutzbar und mit dem Business-Kontext dahinter. Erfahren Sie bei DSAG, wie DEUTZ historische SAP-Informationen und Business-Kontext in seine Daten- und AI-Landschaft einbindet. Treffen Sie Prof. Dr. Christian Hürter, CIO von DEUTZ: 📅 6. Oktober · ab 12:00 Uhr 📍 DSAG · Stand D15

Construction's framework has applied since January 8, 2026, and the product passport requirement is on its way. The companies that will struggle are not the biggest, but the ones where CPR, ESPR, and steel rules land on the same products. One data foundation covers them all.