LinkedIn image ad examples

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

Noka streamlines compliance, saves time, and secures top retailer wins with Crisp EDI. Real-time order intelligence transforms operations.

Your world is moving parts, missed windows, and margins that vanish if one vehicle breaks down. You don’t need another theory; you need a sharper playbook written by people who live your reality. Four times a year, you and 9 other field service executives compare what actually moves numbers in the field—so every decision has real-world evidence behind it, not just a slide deck.

You know that question you only ask yourself at red lights and hotel check‑ins: “Am I the only one holding this whole thing together?” You shouldn’t have to carry that alone. This room is 10 field service leaders who’ve seen the same chaos, made the same calls, and are ready to trade the answers nobody else in your company even knows you need.

🚀 Up to €30,000 in funding to get started with Catena-X Rising customer expectations, new reporting requirements, and fragile supply chains are presenting many companies in the automotive industry with the same challenge: information must be exchanged with partners quickly, securely, and efficiently. Catena-X makes this possible: The dataspace enables companies to exchange data with their business partners according to common standards and rules via unified processes. Most importantly, you retain control and decide what information to share with which partners. The data is neither collected on a shared platform nor managed centrally. Typical applications include the exchange of CO₂ data, quality information, or details on available capacities and demand. Getting started in 2026 is easier than ever: As part of a study by the German federal government, companies receive financial support to establish productive data exchange in Catena-X. Depending on the use case, €15,000 or €30,000 in funding is available to cover initial implementation and setup costs. This offer is particularly interesting for: ✅ SMEs and companies that want to use Catena-X for the first time ✅ Organizations with little experience in the field of data spaces ✅ Teams that want to implement specific use cases, such as Product Carbon Footprint (PCF), certificate management, or the Digital Battery Passport 🏛️ The Data Space Accelerator is funded by the German Federal Ministry for Economic Affairs and Energy and has a total funding budget of 23 million euros. The study will take place exclusively in 2026. Interested? 🔗 Learn more and apply: https://lnkd.in/eRz6K2rv

Attention, automotive industry 🚘: Up to €30,000 in funding to get started with data exchange via Catena-X Learn more now --> https://lnkd.in/eRz6K2rv

Quais riscos sua instituição está assumindo por falta de informação? Uma visão incompleta do cliente pode comprometer a análise e levar à aprovação de operações mais arriscadas do que parecem. A Datahub fornece dados sobre perfil, comportamento e risco para ajudar sua equipe a avaliar clientes com mais critério e apoiar decisões financeiras mais seguras. Clique em Saiba mais e conheça as soluções da Datahub para sua instituição.

Your access model was built for people. Your data estate is serving machines. A data authorization layer is needed for agentic data access.

Your data estate runs different access models across platforms. That gap shows up at audit time when no one can fully explain it.

A problem most construction contractors have: when you ask Finance, Commercial and Ops what a job has cost, you get 3 different numbers. Tellum connects and syncs your data, so you have a single source of truth – and clarity on what’s actually happening across your projects. Get a prototype with your real data in 48 hours. Free of charge. Request now. 🏗

Coupler.io gets every ad account into BigQuery in the time it takes to make coffee. Connect the accounts, pick the columns, set the refresh. Done ✅ Google, Meta, TikTok, LinkedIn — joined into one table, on the schedule you set. No SQL. Start free — 7 days, no card.

Osabudjetit, skenaariot, kassavirtaennusteet ja toteumaseuranta samassa työkalussa. Data yhdistyy automaattisesti kirjanpidosta ja muista järjestelmistä. Fuusor on rakennettu talousjohdolle, joka tarvitsee vastaukset silloin, kun niitä kysytään.

Fuusor on rakennettu kattamaan vaativankin talousraportoinnin tarpeet. Fuusor kerää, yhdistelee ja jalostaa liiketoimintatiedon eri lähteistä yhdelle alustalle – täysin automatisoidusti ja haluamassasi muodossa. Tietoa pystytään myös rajaamaan automaattisesti eri käyttäjien ja tarpeiden mukaan. Visuaalinen palvelu kiteyttää datamassan selkeiksi näkymiksi, raporteiksi ja mittareiksi, joiden avulla pystyt tekemään parempia päätöksiä ja oivalluksia. Tutustu ja varaa demo jo tänään!

Manually moving data from one system to another to keep track of what's going on? 🏗 Try a better way of managing construction projects. No painful migration, no new software – your existing systems, but synced and cut to the chase. See a prototype with your real data in just 48 hours, free of charge. Request now.

300 Beteiligungen. Zwei getrennte Systeme. Ein Single Point of Truth. So hat die Raiffeisen-Landesbank Steiermark ihr Beteiligungsmanagement mit dem Legal Entity Manager von Goldright neu aufgestellt – mit konsistenten, tagesaktuellen Stammdaten und Reporting auf Knopfdruck. Sehen Sie in der Success Story, wie.

Your AI agents just showed up to the party... and they brought thousands of friends. Every agentic workload wants its own database. Multiply that across your whole fleet of agents, and suddenly your infra team is drowning. Enter Cockroach Continuum: built to create, isolate, and run many databases without your infrastructure (or your DBAs) breaking a sweat. Here's how: -> Disaggregated storage scales compute and storage independently. -> Virtual Clusters consolidate isolated databases on shared private hosts. -> Aegis reduces estate-management overhead. We break down Cockroach Continuum's full architecture here: https://lnkd.in/evMdkt_a

Vor Kurzem habe ich mit einem Interessenten unseren ROI Calculator live im Call ausgefüllt. Zehn Minuten, einige Zahlen – und ein sehr stiller Moment auf der anderen Seite. Es ging um eine ziemlich normale Ausgangslage: mehrere hunderttausend Stammdatensätze, sieben Quellsysteme, ein Team, das laut eigener Schätzung „irgendwie“ viel Zeit mit Datenpflege verbringt. Wir haben gemeinsam die Zahlen eingetragen: - Anzahl der Datensätze, - Anzahl der Systeme, die integriert werden sollen, - geschätzter derzeitiger Zeitaufwand pro Woche für manuelle Datenerfassung und Fehlerbehebung, - Kosten für externe Berater, die immer wieder dieselben Aufräumarbeiten übernehmen, usw. Am Ende standen unter anderem vier wichtige Werte auf dem Bildschirm: - der Zeitpunkt, ab dem sich die Investition rechnet, - der ROI über drei Jahre, - die Kosten, die über drei Jahre entstehen, wenn sich nichts ändert, - und der Netto-Vorteil pro investiertem Euro. Keine der vier Zahlen war eine Schätzung von uns. Es waren seine eigenen Zahlen – nur endlich einmal zusammengerechnet, statt über IT-Budget, Fachbereich und Beratungskosten verteilt zu bleiben. Genau das ist für mich der eigentliche Wert der Berechnung mit Hilfe unseres ROI Calculators: nicht ein weiteres Argument für MDM, sondern die Rechnung, die intern sonst niemand aufmacht. Wer diese Rechnung für die eigene Systemlandschaft sehen will: DM oder Kommentar mit „ROI“ und ich schick den Link direkt zum selbst ausprobieren durch.

Apache Spark 4.0 gave you the VARIANT type. It will not make your queries faster. Shredding will. Every post about it says the same three things: no schema, no from_json, 8x faster. Teams are already planning to move their JSON columns over. VARIANT is stored as one binary blob inside Parquet. Parquet is fast for one reason. Every column keeps min and max values per row group, and a filter uses them to skip most of the file without opening it. A blob has no stats for the fields inside it, so your filter skips nothing. Every block gets read, then decoded. You stop paying to parse. You start paying to read. So what is shredding? At write time, Spark pulls chosen paths out of the blob and writes each one as its own typed column, next to the blob. user.id becomes a real BIGINT column with min and max stats. Whatever you did not choose stays in the binary leftover. That is how skipping comes back. The decision: ✅ Still on STRING plus from_json? Move to VARIANT. Clear win. ✅ Already have typed columns in your gold tables? Leave them alone. ✅ Putting VARIANT where people run queries? Shred it, then verify. If the value column still holds binary data for that field, it never got shredded and you are scanning blobs. VARIANT did not delete the cost of JSON. Shredding moves it out of your query path. #ApacheSpark #DataEngineering #Lakehouse

Pokud řešíte, jak z dat vytěžit zlato pro byznys, potkejme se 15. října v Praze na Better Data Evening!🤖 Letos jsme připravili program postavený hlavně na zkušenostech z praxe. Potkáte se s našimi experty i datovými lídry z firem, kde řeší data, plánování a AI v každodenním provozu. Dozvíte se například jak: - jak Národná banka Slovenska staví Open Data platformu - jak PPA Controll využívá AI chatbot nad interními daty a dokumentací - proč AI nad firemními daty někdy selhává a co s tím - jak přední světová antivirová značka dál rozvíjí Business Planning - jak v RS Group probíhá přestavba data foundation za plného provozu Po odborném programu budeme mít prostor pro otevřenou diskusi a networking během společné večeře. 📅 15. 10. 2026 📍 OREA Hotel Angelo, Praha Akce je určena pro: CEOs, CFOs, COOs, CIOs, CDOs, Head of Data, BI a další business, finance, planning a operations leadery. Budu rád, když se na místě potkáme! ☺️ Registrace je zdarma: https://lnkd.in/dNKPxRsh

Máte data. Máte AI. Proč stále neděláte lepší rozhodnutí? To je otázka, kterou otevřeme na konferenci Better Data Evening, 15. října v Praze. Čekají vás konkrétní projekty z praxe, pohledy lidí z vedení firem i diskuse o tom, kde technologie pomáhá a kde samotná technologie nestačí. A nebudeme zůstávat jen u diskuse. Ukážeme čtyři konkrétní projekty z praxe: 👉 Národní banka Slovenska – připravovaná otevřená datová platforma 👉 PPA Controll – AI chatbot v Microsoft Teams nad interními daty 👉 přední světová antivirová značka – další rozvoj plánování a jeho role v řízení firmy 👉 Sellier & Bellot – propojení obchodního a finančního plánování Kromě panelové diskuse Better Decisions tak uvidíte, jak se data, plánování a AI řeší v různých typech firem a situacích. Better Data Evening 15. 10. 2026 | OREA Hotel Angelo, Praha Pokud řešíte data, plánování, AI nebo digitální transformaci, potkejme se v Praze. Podívejte se na celý program 👉 https://lnkd.in/dZ_c2RMr

Bis zu 50 % geringere Integrationskosten und bis zu 10× schnellere Integrationen durch InterSystems – im Kundenprojekt erzielt. Jetzt Zahlen lesen.

Discover where AI can deliver real value and how to scale it effectively. The ICIS Executive Exchange: The Future of AI in Chemicals is an exclusive forum designed for senior decision-makers looking to explore AI's role in commercial performance, operational efficiency, data strategy, and business transformation. Engage in confidential discussions, hear real-world perspectives, and gain practical insight into the opportunities and challenges shaping AI adoption across the chemicals sector.

Erfahren Sie anhand eines Kundenbeispiels, wie moderne Integration Prozesse beschleunigt und die IT finanziell entlastet. Mit einer Datenplattform.

One of the first things I would look at in a CPG Decision Intelligence initiative is a simple decision inventory: what decisions are made repeatedly, who owns them, what data supports them, and what is the business impact of getting them wrong. In CPG, many of these decisions sit around pricing, promotions and short-term supply. But before getting excited about AI or recommendations, the basics need to work: governed data, consistent KPI definitions across functions, and enough traceability to understand how a recommendation was produced and why. For me, this is where the real value of Decision Intelligence starts. Not with another dashboard, but with reducing the time between a signal, a decision and an action. In our new white paper, we look at how to approach this step by step, what to assess first, and where Decision Intelligence can start creating value in CPG: https://lnkd.in/dkYNNRFr