LinkedIn image ad examples

Direct selling moves fast. Your competitive intelligence needs to move faster. New product launches. Market expansion. Distributor strategies. Leadership changes. Regulatory developments. M&A activity. For global direct-selling companies, critical signals can emerge across dozens of markets, languages, and sources—long before they show up in a quarterly report. One global direct-selling leader uses Comintelli’s Intelligence2day® to centralize competitive intelligence, uncover market signals, and give senior leadership stronger evidence for strategic decisions. In one high-stakes case, the intelligence team uncovered evidence that helped mitigate a potential $750M M&A exposure. Imagine giving your strategy team one place to: 🌎 Monitor competitors across global markets 🔎 Detect early signals and emerging threats 📊 Benchmark competitor strategies and outcomes 🤖 Use AI to turn information overload into actionable intelligence 🎯 Deliver decision-ready insights to executives and the board In direct selling, knowing what your competitors are doing is useful. Knowing what it means for your next move is where the advantage begins. 👉 See how Intelligence2day® can strengthen competitive intelligence across your organization. Read the case study: https://lnkd.in/estUxP2C

FlashGrid Cluster is available in the new AWS European Sovereign Cloud, enabling customers to deploy mission-critical Oracle databases, including Oracle RAC, in a fully EU-governed environment. To learn more, visit: https://lnkd.in/dJe7XCcW #HighAvailability #OracleDatabase #AWSArchitecture #AWSInfrastructure #AWSPartner

474 % de ROI, ça s'explique. Le 13 octobre, ceux qui l'ont mesuré (Forrester) et ceux qui l'ont vécu (Workday) vous en disent plus, en direct. 1 heure pour comprendre comment ces résultats ont été obtenus, ce qu’ils représentent concrètement pour les organisations, et ce qu'ils changeraient pour vous.

Everyone's adopted the shiny new AI tools. Not all data teams have the foundations to scale with it - we decided to find out why.

Boomi isn't your only option, and it may not be your best one. We compared the top alternatives so you can see for yourself.

Only 16K of 175K US software companies carry a traditional software label. Most others are classified by the industries they serve—making them much harder to find. ISVWorld helps you uncover this hidden software market and build a more complete prospect list. Build your ISV target list →

Most organizations don’t have an information problem anymore. They have a decision problem. There’s no shortage of dashboards, alerts, reports, summaries, feeds, or AI-generated outputs inside regulated industries today. In fact, most teams are overwhelmed by the volume of information coming at them. But information alone doesn’t create value. Decisions do. And that’s where I think the conversation around “decision intelligence” becomes important, especially in life sciences and regulated environments. Because in these industries, the challenge isn’t simply identifying a regulatory signal or detecting a market change. The real challenge is: ➡️ understanding what it means ➡️ determining who is impacted ➡️ coordinating the right response ➡️ documenting decisions clearly and defensibly ➡️ ensuring actions happen That’s a very different capability than monitoring. What’s becoming increasingly clear is that organizations need systems designed not just to surface intelligence, but to operationalize it. That’s the shift from information management → decision intelligence. And in practice, the companies doing this well tend to focus on a few things: 1️⃣ Connecting intelligence directly to workflows: The most mature organizations are embedding intelligence into operational processes instead of leaving it trapped inside dashboards or inboxes. 2️⃣ Maintaining traceability from signal to action: In regulated industries, every major decision may eventually need to be explained, audited, or defended. Traceability matters. 3️⃣ Combining AI with human expertise: AI can dramatically reduce the manual burden of monitoring, summarization, categorization, and search. But human expertise remains critical for interpretation, prioritization, and accountability. The strongest models aren’t AI-only. They’re human-first systems enhanced by AI. 4️⃣ Creating organizational alignment: Decision intelligence is ultimately about helping teams move faster together, regulatory, quality, safety, compliance, operations, leadership, all working from shared context and trusted information. That alignment is becoming a competitive advantage. One point I think is often overlooked: The future of AI in regulated industries probably won’t belong to generic copilots alone. It will belong to organizations that successfully integrate trusted intelligence, governance, workflows, and human judgment into a repeatable operational system. That’s where a measurable impact starts to happen. We recently explored this topic in more detail, including how decision intelligence is evolving across pharma and life sciences: https://lnkd.in/egXtZ2Eq Curious how others are thinking about this shift. Are you seeing organizations move beyond monitoring toward true intelligence activation and decision support? Or are most teams still stuck at the “information overload” stage?

A few weeks ago I spent a full day in New York with the team from Trace3, Qlik's New Partner of the Year, talking through what the next 12 months of this partnership look like. We had a simple goal for our day together: to leave the room with our top three strategic objectives and a plan to action them. It might come as no surprise that AI readiness made it onto the list, including dynamic technologies like Iceberg and Open Lakehouse. Helping customers figure out how ready (or not) their data management, governance, and preparation are for AI projects is a critical first step. So with Trace3, we're now making sure that's part of the conversation from day one instead of an extra step later on. I really liked the way one of the Trace3 leaders summed up their role: "Our customers pay us to be agnostic, but to have an opinion." That's the responsibility of a good partner. With their data and analytics practice growing 100% year over year (wow!), it seems we're not the only ones who think they're great to work with. Special thanks to Susie LeMay for playing host and expertly guiding the discussion, Hayden Ng for leading from the Qlik side, and Asher Lohman, Scott MacConnell, Kevin Rogers, and Frank Matteson at Trace3 for being such a pleasure to work with. Looking forward to all of the great things to come!

Tired of single-product vendor conferences? They're boring! 6 years ago I came up with an alternative: OSA Con. https://osacon.io. It's anti-hype, practical, and intellectually diverse, with speakers on open source, AI, and analytics. And we invite you to join us on November 2nd for our first in-person conference at the AWS Loft in Downtown San Francisco. There will be 20 awesome talks from awesome engineers at Firebolt, Databricks, IBM, Gamebeast, Grafana Labs, Dremio, Salesforce, Loophole Labs and many others. We have two tracks across the entire day with plenty of time to network and have great hallway conversations. Did I mention that it's free? Can't make it to San Francisco? No problem! The conference is streamed as well. I'll be introducing our speakers over the next few days. Don't wait, though. Tickets are going fast. Sign up today! We'll see you at OSA Con! p.s., Huge thanks to Amazon Web Services (AWS) for the space to run the conference. Y'all are awesome. #OSACon #opensource #ai #lakehouse #databases #cloud

Built-in separation of storage and compute is a key feature of every modern analytic database...Except for open source ClickHouse®. We are changing this today. I'm delighted to announce that Altinity, Inc. Antalya 26.6 builds now offer experimental Content-Addressable Storage (CAS) for MergeTree tables. With a simple configuration change, users can place MergeTree data on shared object storage. The door is open to even faster and more cost-efficient insight on large data sets. There's no lock-in: CAS is 100% open source. Our CTO Alexander Zaitsev has written a blog about the innovative design behind CAS and how to enable it yourself. https://lnkd.in/eaMUz3is. Altinity customers are already lining up to try it. CAS is still experimental. It passes our internal tests--which are extensive. What we need now is feedback on real world systems. We invite you to install Antalya and give us feedback. Our plan is to release a GA version of CAS by the end of 2026. It will join a host of Antalya features like OAuth/OIDC integration, swarm servers, plus high-performance export to and query from Iceberg data lakes. We're building the open source foundation for the fastest, most cost-efficient analytics on the planet. Help us get there. Try out CAS today! #opensource #realtime #analytics #antalya #clickhouse

AI is the most hyped technology of my 30+ year career, but I think it's significantly under-hyped when it comes to how drastically it'll transform the way businesses run. Most companies are still just using AI as an assistant that helps them write messages, summarize meetings, build a chart, etc. The bigger impact comes when AI starts making business decisions. I have gotten a lot of pushback when i've said this before, and it usually sounds like "judgment should remain with humans." But AI is faster and its memory is greater than the sum of an entire team's. And with the right system, AI can make even complex decisions, while humans focus on the ones that need them (and system design.) I'm seeing this happen in startups & smaller tech firms now. A startup building on AI from day one doesn't carry the baggage of how things have always been done. But, in nearly every market, I think someone will eventually get to 10x the output at 1/2 the headcount, if they haven't already. Therefore, every company is going to need to think this way in order to compete against new entrants in their space. Getting there takes two things: 1️⃣ Process. Companies need processes people actually follow, documentation that explains them, software that facilitates (or runs) them. Processes make a business measurable. 2️⃣ Full history. A record of everything that happens, from sales calls to meeting transcripts, to competitive research, to project plans to marketing, sales, operational, financial, etc data. This makes a business visible to AI and the team. With these two things in place, agentic analytics can do analysis and make (or suggest) better decisions, faster and far more frequently than humans. With agentic analytics, companies can be more agile, making decisions that used to take a quarter or a year within a week or a month. To help companies get here, I've developed an assessment. I've run it a few times now. Here's what I've seen so far: Nearly every company starts out fragmented, with numbers spread across systems that define them differently and someone assembling (or inspecting) them by hand every time. From there, the curve to an autonomous business has 4 stages: 1️⃣ Aggregated (visibility): All performance data & business context pulled into one place. 2️⃣ Governed (measurability): One source of truth, agreed definitions, and a target for every function. 3️⃣ Predictable (foresight): The business knows which activities produced which results, and can model what a change would do. 4️⃣ Autonomous (autonomy): Systems analyze and suggest work or act on their own. If you're curious where you stand, the assessment is free. It takes an hour, and you leave with a written report built at the end of the call. If you are one of the first few that respond to this, I'll be running the assessment. https://lnkd.in/guuB5uuk

„Agentic Sales ist spannend. Wir beobachten das erst einmal.“ Der Satz fiel im letzten Strategiemeeting. Das ist nachvollziehbar. Niemand möchte mit einem schlecht gewählten KI-Projekt Zeit und Budget verbrennen. Beim nächsten Meeting fällt derselbe Satz wieder. Ein Verantwortlicher fehlt weiterhin. Ein konkreter Versuch auch. Währenddessen bleibt der Vertrieb nicht stehen. Nur die Arbeit bleibt liegen. Nachfassaktionen versanden. Kundensignale aus CRM, E-Mails und Gesprächen werden nicht genutzt. Die Vorbereitung auf den nächsten Termin beginnt wieder bei null. Das Problem daran: Diese Verluste tauchen selten als eigene Position im Bericht auf. Niemand schreibt in eine Zeile, wie viele Chancen durch späte Reaktionen oder lückenhafte Vorbereitung verloren gingen. Ein Pilotbudget dagegen fällt sofort auf. So entsteht eine merkwürdige Sicherheit. Das sichtbare Budget wird vermieden. Die unsichtbaren Kosten laufen weiter. Die unbequeme Zuspitzung: Wer jeden Versuch verschiebt, verschiebt auch die Erkenntnis, was im eigenen Vertrieb funktioniert. Der bessere Weg beginnt nicht mit einem großen Programm. Wähle einen eng begrenzten Prozess. Zum Beispiel das Nachfassen nach einem Angebot, wenn innerhalb von drei Tagen keine Reaktion kommt. Erfasse vorher die Ausgangswerte: Zahl der Nachfassaktionen, Reaktionszeit des Teams und daraus entstehende Gespräche. Dann starte einen überschaubaren Versuch. Ein Agent bereitet die nächste Aktion vor. Der Mensch prüft und entscheidet. Erfolgskriterien, Laufzeit und Abbruchregeln stehen vorher fest. So wird aus Beobachtung eine belastbare Entscheidung. Vielleicht funktioniert der Ansatz. Vielleicht muss er angepasst werden. Beides ist wertvoll, weil es die eigene Realität abbildet und nicht die Folie eines Anbieters. Ein überschaubarer Einstieg liefert eigene Erfahrungen. Genau die fehlen im nächsten Strategiemeeting sonst wieder. Wenn du in einem zehnminütigen Video live sehen willst, wie Agentic Sales zum Turbo im Vertrieb wird, schreib mir eine private note mit „NICHT MEHR WARTEN“. Ich sende dir den Videolink.

11 Excel-Dateien, fünf Verantwortliche, eine Wahrheit. Die Wahrheit war nirgendwo. Bei einem Kunden lief die operative Steuerung über elf Excel-Dateien. Jede beteiligte Abteilung pflegte ihre eigene Version. Fünf Menschen trugen Verantwortung, doch niemand konnte verbindlich sagen, welcher Stand galt. Die Dateien waren nicht zwingend falsch. Sie beantworteten nur jeweils einen Ausschnitt. Das Problem entstand an den Übergängen: unterschiedliche Definitionen, unterschiedliche Aktualisierungszeitpunkte, unterschiedliche Annahmen. Elf sauber gepflegte Ausschnitte ergeben noch kein gemeinsames Bild. Wir haben die Daten in eine zentrale Struktur überführt. Technisch war das lösbar. Die eigentliche Arbeit begann danach. Wer pflegt welche Kennzahl? Bis wann? Wer prüft Abweichungen? Wer entscheidet, wenn zwei Bereiche unterschiedliche Werte melden? Und welcher Stand gilt ab Montagmorgen? Die fünf wichtigsten Learnings: 1. Eine gemeinsame Datenbasis braucht eine gemeinsame Definition. Sonst werden nur elf Widersprüche an einem Ort gesammelt. 2. Jede Kennzahl braucht eine fachlich verantwortliche Person. Nicht jeder ein bisschen. Eine Person muss verbindlich zuständig sein. 3. Aktualität muss geregelt sein. Ein Wert ohne Stichtag ist keine Steuerungsinformation. 4. Abweichungen brauchen einen Eskalationsweg. Sonst gewinnt im Meeting die Datei mit der überzeugendsten Formatierung. 5. Entscheidungen brauchen einen klaren Prozess. Daten zeigen etwas. Handeln muss danach jemand. Excel war nicht der Bösewicht. Für einzelne Aufgaben ist es schnell, flexibel und völlig ausreichend. Kritisch wird es, wenn aus vielen lokalen Werkzeugen unbemerkt ein gemeinsames Steuerungssystem werden soll. Eine zentrale Plattform allein löst das ebenso wenig. Ohne Rollen, Definitionen und Entscheidungsregeln entsteht aus elf Dateien nur ein sehr ordentlich zentralisierter Streit. Wenn du prüfen willst, ob deine operative Steuerung auf einer gemeinsamen Wahrheit beruht, schreib mir. In einem kurzen Steuerungs-Check klären wir Datenquellen, Verantwortungen und Entscheidungswege.

Z nostalgie si ho sem tam pustíte. Ano bylo by to na mobilu jednodušší, ale když máte čas a náladu tak proč ne. Co ale v kanceláři? Tam si ho do sluchátek nezapojíte. Nebo třeba v autě? Tam je rádio výrazně praktičtější volba. Někdy je prostě třeba upgradeovat a ve světě technologií bylo včera pozdě.

Poštovní holub byl kdysi nejrychlejší způsob doručení. Spolehlivý, prověřený, nikdo si nestěžoval. Dneska by ho nikdo nepoužil. Přesto většina firem má aspoň jeden proces, který je přesně takový holub. Funguje. Jen strašně pomalu. Který je to u vás?

We have been doing a lot of work in the background on our platform 🐄 🛠️ Watch this page for more info coming your way soon...

Are your existing address records ready for ISO 20022? We can structure them into the hybrid format and return ready to import into your systems.

Our Address Capture API returns every address in the ISO 20022 hybrid format. See how it works and book a free data assessment.

Win more customers and earn higher margins with DS3 Composer: software-defined S3 Object storage for the Al era. Deliver flexible SLA/pricing tiers from a single intuitive console, with full sovereign control and low IT overhead.

Flexible S3 storage that gives you the freedom to build the right offer for every customer. Up to 50% higher margins vs. traditional S3. 100% European.

Why wait for recovery audits to tell you where money leaked out? With data² reView™, you check every charge as it comes in—field service invoices, capital change orders, shared costs and billing runs. One midstream operator uncovered $8M in incorrect and unbilled invoices in a month. You could be surfacing hidden exposure in the first weeks.

Your team approves thousands of field service invoices a month and checks a sample. The rest gets paid at month-end. That's how an invoice like this one gets through. Three-way match never sees the field ticket or the rate in force on the work date. reView™ checks every charge, not a sample, against the records you already have. No data migration. No new ERP or consolidation.

We have been doing a lot of work in the background on our platform 🐄 🛠️ Watch this page for more info coming your way soon...

As your SQL Server estate grows, quality should not depend on who happens to know it best. That is a systems problem, not a people problem. DB24 checks, documents and reports on every instance the same way, every day, so the picture stays complete as the estate grows and the next person can pick it up.