LinkedIn image ad examples

What is AI actually doing to search? Our Q2 report uses behavioral data to separate measurable change from industry speculation.

AI kept growing in Q2. But what happened to traditional search? See what real clickstream data reveals in our latest report.

Your reps stop guessing and start closing. DashLeads scores every bar, restaurant and venue 1 to 100 based on fit for your product.

DashLeads pulls data from Google Maps, delivery platforms, social signals and more so your rep already knows the venue before the first handshake.

Snowflake or Databricks. dbt. Airflow. CI/CD. Developer environments. Reliable Data. Trusted AI. As the stack grows, so does the operational overhead. At dbt Summit, we're doing something simple: Bring us your current data stack and spend 15 minutes with Noel Gomez, co-founder of Datacoves. We'll talk through what's working, where you're carrying unnecessary complexity and what we'd change. No hour-long sales presentation. Just a practical conversation about your architecture. Book your slot now and meet us at the Datacoves booth in Las Vegas.

GTM for the local economy requires a completely different playbook. Unlike traditional B2B GTM, selling into hospitality, home services, healthcare, and other local verticals has always lacked the data infrastructure to make TAM mapping, scoring, intent, and contact coverage actionable. With AI, that gap is closing. The best sales teams in local verticals are scaling faster than ever. Excited to be doing a deep dive into this topic on the GTM panel at Vertex: The Vertical Software Conference. Highly recommend you check out the event if you're in the Bay Area on Tuesday!

You’ve got the content. We’ve got the buyers. Defined.ai connects companies with the AI world that’s hungry for real, diverse human data — ethically and at scale.

Imagine if your user content could moonlight as AI training data — no shady data deals required. Defined.ai helps you monetize responsibly, keeping ethics and consent front and center.

It reaches policymakers. Empowers communities. Drives real-world change. Explore how Darkhorse Visualization transforms rigorous research into compelling, decision-ready visuals.

How far does your research travel after publication? Far enough to change conversations? Shift funding? Shape policy? We help leading researchers make their work both accessible and unforgettable.

Find signals, prevent drop-offs, and build smarter re-engagement flows with actionable retention insights.

Learn what top LiveOps teams do to drive session frequency and keep users around longer.

We've been working on something useful with our friends at n8n 🚀 In the upcoming webinar on December 4th, we'll show you how to build automated workflows for system monitoring, security tracking, and brand mentions using our very own Decodo node. You can easily learn more and later get 5000 free requests with our Scraping API product! Register here -> https://lnkd.in/dgt6CtXx

🔥 The SOC you built is about to become obsolete 🔥 Data volumes are exploding. AI promises are everywhere. But here's what nobody's telling you: if you don't own your data layer, you don't control your future. 2026 isn't about bigger platforms. It's about who controls the telemetry that powers detection, automation, and intelligence. Join us for The 2026 Security Data Reckoning: Taking Back Control of Your SOC: a fireside chat with industry analysts Francis Odum and Aqsa Taylor from Software Analyst Cyber Research (SACR), alongside Databahn's Co-Founder Nithya Nareshkumar and CPO Aditya Sundararam Click 'Attend' here and book your front row this to the discussion of the year! https://lnkd.in/gjXHkYdA

I often get asked why local economy? The answer is simple - it’s a massively underserved market. 99% of sales tools are designed to sell to office workers. This is no knock on LinkedIn Sales Nav or ZoomInfo, those tools are great if you’re selling to tech companies or F500. The challenge is if you sell into restaurants, the trades, brick-and-mortar retail, healthcare providers, or any other mainstreet business - these companies and individuals simply do not exist on LinkedIn or in traditional databases. They are ghosts on the internet. As a result, sales reps in these industries spend 20-40% of their week on manual research - making it nearly impossible to hit ambitious revenue goals. The good news is it’s finally possible to solve this problem. Unstructured data algorithms are now intelligent enough to map an incredibly noisy web of online, offline, and proprietary data sources. The best companies are already automating this research away, freeing up reps to focus on selling. Over the next few weeks, I’m excited to start sharing more examples of how they’re doing it and what it means for the future of GTM.

Run your workloads on Spark - Supercharge it with DataPelago accelerator.

10x Faster Spark. 80% Cost Reduction. 0 Code Changes. Yes, really. This isn't just another plugin that requires you to rewrite your pipelines. Drop-in DataPelago Nucleus which: - Integrates at the Spark Catalyst level. - Recompiles for end-to-end GPU execution. Your Data frame ops, SQL queries, and ML pipelines just got 10x faster and 80% cheaper. No code changes.

Get a clear framework that will help you to evaluate data quality. 6 steps to better insights + a checklist

Can you trust the voice recording data used for reporting and analytics? CC1 reconciles data across multiple systems in near real-time, delivering clean, validated voice recording data with unrivalled accuracy.

Most HubSpot CRMs I've seen are half-empty. Sales reps manually researching company size, headcount, industry. Guessing on ICP fit. Spending hours on accounts that were never going to close. So I built a workflow to fix it. 👇 Using the Coresignal n8n node, every new company created in HubSpot now gets automatically enriched with multi-source B2B data – no manual research, no stale records. Here's how it works: → A new company is created in HubSpot → A short delay ensures the record is ready → Coresignal fetches enriched company data in real time → HubSpot is updated automatically Took me 10 minutes to build. Saves the team hours every week. If your reps are doing this manually, they shouldn't be. Workflow 👉 https://lnkd.in/g-Za2x9B #CRMenrichment #salesautomation #B2Bdata #n8n #coresignal #hubspot

If you ship apps on Huawei devices in China — and increasingly you have to — you've probably noticed something: most international product analytics platforms quietly skipped HarmonyOS. Mixpanel, Amplitude, Firebase, PostHog, Heap — none of them currently offer a native HarmonyOS SDK. Your options have effectively been Huawei Analytics Kit (locked into AppGallery Connect, data sits with Huawei) or domestic SaaS vendors like Sensors Data and GrowingIO. Today we're adding a real third option. Countly v26.1.0 for HarmonyOS is live on GitHub. It ships at near-parity with our Android SDK from day one: → Events, views, sessions → Crash reporting → User profiles → Consent management → Device ID, location → Remote Config → SDK Behavior Settings → Crash analytics Why this matters for teams shipping apps in China: 1️⃣ Self-hosted or private cloud. Run Countly on your own infrastructure inside China. Your HarmonyOS event data never leaves your servers. No third-party SaaS pipeline, no AppGallery Connect dependency, no cross-border data transfer concerns under PIPL. 2️⃣ One platform across Android, iOS, Web, and HarmonyOS. Same event taxonomy, same dashboards, same SDK API surface. No fragmented stack, no separate vendor just for HarmonyOS. 3️⃣ Product analytics + engagement in one place. Not just events and funnels — also crashes, user profiles, remote config, and (in upcoming releases) the rest of the Countly engagement layer. HarmonyOS is now China's #2 mobile OS, with 55M+ native devices and ~17% share. The teams who'll get ahead are the ones treating it as a first-class platform — not an afterthought. If you're a HarmonyOS developer or a data team responsible for understanding how Huawei-device users actually behave in your product, this is for you. Check the SDK: https://lnkd.in/d_ie-BXW See our Docs: https://lnkd.in/dBNGvThM #HarmonyOS #ProductAnalytics #MobileAnalytics #Huawei #DataPrivacy #OpenSource #Countly

The Kafka agent isn’t the moat. The context and permissioning layer around it is. A capable model is useful, but it doesn’t operate in a vacuum. In production, the hard part is the surrounding system: what the agent can observe, what it can reason over, and what it’s allowed to change. In Kafka, that means more than seeing a lag spike. It means understanding schemas, lineage, ownership, ACLs, recent changes, and how services depend on each other. Without that context, the agent’s guessing. Without the right permissions, it’s a faster path to an outage. That’s where agentic Kafka operations gets interesting: not just better agents, but better context and control around them.

Every team and AI agent touches your Kafka. Who controls what they access? Conduktor governs both, on the Kafka you already run.

The speed of cloud analytics. The control of self-hosting. For years, enterprises have been forced to choose: the performance of cloud analytics, or keeping customer data inside their own environment. Countly 26.01 is our answer to that false tradeoff. A new analytics engine built to analyze millions of users, power real-time personalization, and run AI-driven experiences — while behavioral data stays in your infrastructure. → Up to 100M monthly active users → Self-hosted or private cloud → GDPR, HIPAA, SOC 2, CCPA-ready by design Learn more about the new architecture here: https://lnkd.in/d-HM9K4W #analytics #dataprivacy #enterprise #selfhosted