Ernesto Ongaro
Dublin, County Dublin, Ireland
3K followers
500+ connections
View mutual connections with Ernesto
Ernesto can introduce you to 10+ people at Omni
or
New to LinkedIn? Join now
By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy.
View mutual connections with Ernesto
or
New to LinkedIn? Join now
By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy.
Articles by Ernesto
-
Five Takeaways from Microsoft's Fabric Conference
Five Takeaways from Microsoft's Fabric Conference
I had the opportunity to attend the European Microsoft Fabric Community Conference in beautiful Stockholm, Sweden. With…
84
-
Your Company Could be More like Looker.Jul 27, 2017
Your Company Could be More like Looker.
10 days into my new role at Looker, I share 5 things that I love about being part of the team here so far. 1.
81
6 Comments -
4 Embedded BI PredictionsJan 5, 2017
4 Embedded BI Predictions
Prediction #1: Embedded BI goes Ubiquitous: embedded BI will go from being a niche product used by software companies…
30
3 Comments -
The Heart of IoT: Data AnalyticsFeb 3, 2016
The Heart of IoT: Data Analytics
Every large-scale technological breakthrough is accompanied by a data delivery breakthrough. This has been true in the…
26
Activity
3K followers
-
Ernesto Ongaro shared thisHello folks, if you're an Omni customer, or just curious what we've been up to lately, please tune inErnesto Ongaro shared thisJoin Jade and Jack from our product team for an inside look at the latest AI features. We’ll cover how to: - bring Omni into other tools like Claude, ChatGPT, & Slack - build dashboards & apps from simple prompts - manage suggestions & run evals in the AI Hub Session starts this Wednesday (June 24th) @ 10 AM PT. We’ll take live questions, and we hope to see you there 👉 https://luma.com/6mpap99j
-
Ernesto Ongaro shared thisSo a few you of you reached out after my Omni Dashboard Builder demo and said what I made was a bit basic and not realistic...fine! Here's something a bit more surgical, Blobby nails it!
-
Ernesto Ongaro shared thisWell. Big day. The World Cup starts and at Omni we have released our ✨Dashboard Builder. Obviously we’ve had a regular point and click builder since day one, this is different. Describe what you want, and Omni builds it for you based on all the logic and permissions in your semantic layer. Then you review, refine, and publish when you're ready. Make that taller. Add a KPI. Change the chart type. Whatever you need. If you’ve ever built or maintained a dashboard by hand, this one is for you!
-
Ernesto Ongaro shared thisLa scaloneta ya llego! ⚽⚽ I watched Maradona lift the trophy in Mexico in 1986 and Messi in 2022. Back then we made our picks on pure faith and one very good number 10. This year you can do better. My colleague Peter Whitehead built Blobby's World Cup Bracket Challenge, a bracket app with live player stats, head-to-head records, and an AI agent you can interrogate before every pick. Make your picks with data instead of vibes: @ https://blobbyworldcup.com I'm still picking Argentina 🇦🇷 though. Some things aren't up for analysis. Quiero ver la cuarta ⭐⭐⭐⭐!
-
Ernesto Ongaro shared thisHey London peeps. Chris Merrick, Will Savage and myself will be attending, hope to see you there!Ernesto Ongaro shared thisI'm speaking at Anthropic’s Code with Claude event in London on May 20th. The session is on the agent harness we built for analytics: what we let Claude see, what we make it validate, and where Claude Code sped things up. If you're there, come find me. https://lnkd.in/eUhtjY9D
-
Ernesto Ongaro reposted thisHappy to be speaking at the upcoming Snowflake Stockholm User Group meetup ❄️📊 I’ll be sharing a few lessons from our work on finance and data challenges at 0TO9 | Bank of Entrepreneurship where finance and data meet in one place…and occasionally disagree 😄 We’ll look at how we’ve built reconciliation, P&L, and performance risk monitoring powered on Snowflake, dbt Labs and Omni and how “why don’t these numbers match?” is often less a spreadsheet issue and more a data platform story. Because every finance problem eventually turns into a data challenge 🚀 Looking forward to great conversations and meeting the Stockholm data community ❄️ Will also try to keep the spreadsheet jokes to a reasonable level… no promises 😄Ernesto Ongaro reposted this🚀 We’re excited to announce the next Snowflake Stockholm User Group meetup, this time focused on Finance & Data. ❄️🇸🇪 Join us for an evening exploring how organizations are leveraging Snowflake to modernize financial operations, improve trust in data, and accelerate decision-making in a highly regulated industry. Sign up here: https://lnkd.in/dybtMacK 🎤 Featured talks: 🎤 Transforming the Office of the CFO with Data & Technology by Matthew Jolliffe from Spaulding Ridge 🎤 From Transactions to Trust: P&L, Risk & Recon on Snowflake by Manish Ramrakhiani from 0TO9 | Bank of Entrepreneurship 💡 Whether you work in finance, analytics, governance, or enterprise architecture - this session is designed to deliver practical insights, modern data strategies, and great discussions with the Stockholm data community. Seats are limited, and we’d love to see a strong mix of finance and data professionals in the room. 👉 Join us and be part of the growing Snowflake community in Stockholm. Emma MacGregor Fredrik Viksten #Snowflake #SnowflakeUserGroup #Finance #DataEngineering #CFO #FinTech #Analytics #StockholmTech #snowflake_advocate #datasuperheroFinance Meets Data: Snowflake Stockholm Meetup | Snowflake User GroupsFinance Meets Data: Snowflake Stockholm Meetup | Snowflake User Groups
-
Ernesto Ongaro shared thisDo you want to learn Omni from the best? Join Peter Whitehead on DataCamp's live hands on lab tomorrow!Ernesto Ongaro shared thisDashboards aren't going anywhere, but they should do a lot more to surface insights and help stakeholders make decisions faster 📊 Tomorrow, DataCamp is hosting a code-along webinar with Omni's Peter Whitehead on building AI-driven dashboards. You'll work through a real dataset, design and structure a dashboard in Omni, and learn how to add AI features that make analysis faster and more useful for stakeholders. 🗒️ Friday, May 1 @ 8 AM PT / 11 AM ET 🎟️ https://lnkd.in/gFAYwMwb
-
Ernesto Ongaro shared thisGUIs beat CLIs for forty years because humans needed pictures. Agents don't. Great post from Nathan Agrin on why a CLI is the right interface for the next wave of data work 👇Ernesto Ongaro shared thisIntroducing the Omni CLI — a simple, but highly capable tool built for AI agents and developers. For AI agents, the Omni CLI is the semantic bridge to your governed data. Easy to self-discover, read, and bound to the same permissions as the user who invoked it. Check out the demo from Ernesto Ongaro for an overview, and read the blog from Nathan Agrin to learn how he built it and what surprised him along the way: https://lnkd.in/gx_kWmKu
-
Ernesto Ongaro shared thisEvery number in our Series C story was written by a customer. The data teams who pushed for more. The analysts who use us daily. The users who started asking Blobby questions their BI tool never let them ask. You're the reason this round happened. Thank you. Now back to building.Ernesto Ongaro shared thisToday, we're announcing a $120M Series C at a $1.5B valuation, led by ICONIQ with participation from Theory Ventures, First Round Capital, Redpoint, and GV (Google Ventures). To our customers, partners, investors, and our entire team — thank you for building this with us 🩷 Read the full note from our CEO, Colin Zima 👉 https://lnkd.in/dSTyN5iW
-
Ernesto Ongaro liked thisErnesto Ongaro liked thisEvery data tool now has a thin wrapper around Claude to write SQL. Claude Code and Codex have changed how everyone is working. It's so easy to build everyone is. Vibed applications, vibed analysis, and obviously vibed dashboards. Every data team is having to grapple with: Why not just point Claude at the warehouse? Do we need BI at all? The analogy to me is actually Excel. Even pre-LLM, when data is locked up and hard to get, life will find a way. Users will just export the data locally. They slice and dice it on their machine and find immediate value. Data teams struggle with this democratized access because of inconsistency. At the end of the quarter, the CRO, CMO and CFO are arguing about whose numbers are right and what do they actually mean. Data people are becoming arbiters of truth. They are forced to look at every vibed analysis, as they used to look at Jamie's Copy of a Copy.xlsx to figure out what was filtered, what logic was applied. When ease of use is the primary feature, everyone will use it, whether it's a modern agent automating the work or the old fashioned way in spreadsheets, with manual SQL, or drag and drop interfaces. This will inevitably lead to inconsistency and duplicated efforts. ARR and churn will be redefined and re-derived over and over again. Most knowledge workers can use Excel, everyone can use chat. Omni started with the intention to bridge easy ad hoc analysis leveraging governance. The best of both worlds. Today that means as easy as Claude for data, deeply integrated into a semantic model with AI context. It's more accurate, much more token efficient with deterministic execution and security. Integrating AI deeply into enterprise BI means you get the value of AI and all the unsexy functionality of a SaaS platform, permissions, change management and audit-ability. Each new model makes the system smarter, faster, cheaper. Claude Code can already read a schema and write good SQL. A thin wrapper was never going to be defensible. Your definitions, your context and the system to build them. That part is yours.
-
Ernesto Ongaro liked thisErnesto Ongaro liked thisArielle Strong just dropped a new blog post on Suggestions and Evals in Omni's AI Hub. Check it out!👇
-
Ernesto Ongaro liked thisErnesto Ongaro liked thisYou can't check every question your agent answers by hand. AI means your data team no longer writes every query. But you still need visibility into what the agent does, and control over the outcomes it produces. A handful of questions turns into thousands fast. That takes tools built for scale, not more manual review. That's why we built AI Hub with Suggestions and Evals. Suggestions turn real usage into model improvements. Evals let you test how the agent handles a change before it ships. Arielle Strong, our VP of Product, breaks down how to run your agent like a data product 🔗 https://lnkd.in/gKyEx2yp
-
Ernesto Ongaro reacted on thisErnesto Ongaro reacted on thisWe built our own AI analytics context on vibes for the first few months. Colin and I would spend a whole day asking questions, reading the agent’s answers, tweaking context, repeat. It didn’t scale. More questions than we could spot-check by hand. More datasets, each with its own logic and edge cases. And the stakes kept rising- our employees were using the Omni Agent’s output to make real decisions. So we built AI Hub for ourselves first: to see what people were actually asking, to get an agent to help us spot patterns, and to replace vibe checks with real test cases. Now, when we want to try a new model, tune a config, or test an idea- we open a branch, run the eval, and know before it ships whether we made things better or worse. Vibe checks still have a place (and we still do them!). But some answers run the business, and those need more than vibes. The full writeup and how you can try it yourself: https://lnkd.in/eAqEWXYP
-
Ernesto Ongaro liked thisErnesto Ongaro liked thisYour coding agent knows SQL. It doesn't know how your team does dbt. dbt Labs Labs just open-sourced a collection of Agent Skills that turn generalist agents (Claude Code, Codex, Cursor…) into actual analytics engineers — encoding the workflows, tests, and conventions the community has spent years refining. Covers analytics engineering, the semantic layer, platform ops, and Core → Fusion migration. On ADE-bench, accuracy climbed from 56% → 58.5%, with the biggest gains on iterative DAG work. Great writeup by Joel Labes and Jason Ganz on the dbt Developer Blog 👇
-
Ernesto Ongaro liked thisCan't wait to try this out — hoping this cuts out a lot of the use cases where I'd normally check the dbt Docs
-
Ernesto Ongaro liked thisErnesto Ongaro liked thisComing up on a year at dbt Labs. Same question everywhere in South Africa this week: how do we make our data ready for AI? Great week at DataFest Joburg with Fivetran and dbt Labs now one team, focused on trusted, open data infrastructure for AI. #DataFest #SouthAfrica #AI Anouar Hnini John Woods Poonam A. Zahoor Ahmed James Fletcher
-
Ernesto Ongaro reacted on thisErnesto Ongaro reacted on thisOne year at Doppel complete and if this first chapter is any indication, we are just getting started. Every month brings something new. Between product launches, a complete rebrand and website refresh, global campaigns, major industry and customer events, new content and cheering on the Knicks all the way to a championship, it's been a rewarding and wild ride. The real highlight has always been the culture and dedication of the Doppel team. This past week in Denver with the marketing team was inspiring and high-energy as we planned what's next! I’m incredibly grateful to work with these incredible marketers and everyone here as we scale Doppel globally to protect organizations from social engineering attacks every day. Here’s to another great year! 🚀 (We're still growing! If you want to build the future of cybersecurity, check out our open roles in the comments.)
-
Ernesto Ongaro reacted on thisErnesto Ongaro reacted on thisWith SYNQ being acquired, and deciding to call time on my journey there, I had time to think about the next adventure. In truth, I planned on taking a few months off to assess. Then I met Shun Pang & Rachel Mumford. I’ve worked for some special companies in my time, but truth be told I can’t say I was ever deeply connected to the mission: cloud compute, payments, data, and networking wouldn’t be what I’d term ‘inspiring'. Anima's goal is to build the holy grail of human wellbeing through personalised medicine: a platform that predicts health issues before symptoms show up, and builds a care plan ultra-tailored to the individual, down to their genomics. With 1,200+ GP practices using Anima today, serving 25% of the UK population, and international expansion on the horizon, we're well on our way to achieving this. It's a privilege to be joining this crew on that mission. Abú.
Experience
Education
Licenses & Certifications
Languages
-
English
Native or bilingual proficiency
-
Spanish
Native or bilingual proficiency
Recommendations received
7 people have recommended Ernesto
Join now to viewView Ernesto’s full profile
-
See who you know in common
-
Get introduced
-
Contact Ernesto directly
Other similar profiles
Explore more posts
-
Clari
122K followers
If insights were enough, everyone would be hitting quota. But 67% of sellers fell short last year 🚨 Why? Because fragmented data, guesswork, and disconnected tools leave even the best teams flying blind. In his latest blog, Rob Webster, Enterprise AE at Clari, breaks down what’s actually working for top-performing sellers — and why Revenue Context™ is the key to turning AI insights into execution. Find out: ✔️ Why your AI is only as good as the data it understands ✔️ How reps can run their territory like a CRO ✔️ What top managers are doing to close performance gaps Learn how to sell smarter, not harder: https://clari.to/uiD0k
15
2 Comments -
Soumya Surabhi
GTM Walnut • 9K followers
In most RevOps and sales environments, the act of assembling context routinely takes 3 - 5 minutes per decision: - Opening a deal - Scanning recent emails and calls - Checking lifecycle status and last activity - Determining whether a follow-up, task, or update is warranted Individually, this feels negligible. Systemically, it’s expensive. When multiplied across: - Dozens of daily micro-decisions per rep - Hundreds of deals or contacts in flight - Weekly pipeline and follow-up reviews Context assembly can quietly consume multiple hours per rep per week; time spent reconstructing state rather than advancing it. That cost shows up as: ❌ Slower follow-ups ❌ Missed signals ❌ Inconsistent pipeline hygiene Long before volume or scale become the problem. Re-anchor to Claude + HubSpot This is why integrations like the Claude connector inside HubSpot start to matter. Not as background automation, but as decision-time context compression. With the connector enabled, Claude can access HubSpot objects directly inside the chat interface - contacts, companies, deals, lifecycle stages, emails, calls, meetings, tasks, and notes, without exporting data or switching tools. Instead of: open → scan → summarize → decide → act Teams move toward: query → reason → review → write The practical benefit isn’t “AI productivity gains.” It’s fewer human steps per decision. - Fewer tabs opened - Fewer manual summaries written - Fewer missed or delayed follow-ups due to context loss Even if each decision saves only 1-2 minutes, the aggregate effect across a GTM team compounds quickly. The time saved doesn’t disappear. It reallocates to: ✅ Higher-quality follow-ups ✅ Better prioritization ✅ Faster pipeline movement This doesn’t replace workflows, scoring models, or orchestration layers. Claude operates between insight and execution, inside the CRM itself: - Compressing context - Reducing decision latency - Preserving human review on writes Fewer steps. Better context. Faster decisions, using the data that already exists in HubSpot.
80
11 Comments -
Corpridge
146 followers
💡 Why PE-Backed SaaS Companies Struggle to Scale RevOps & GTM and How to Fix It? If you lead a PE-backed SaaS business, you’ve likely felt the growing pressure to scale revenue fast, while keeping efficiency, predictability and performance intact. But here’s the truth: it’s rarely the product, the market or the talent that holds growth back. It’s the operating system of growth itself; your RevOps and GTM infrastructure. 🚨 The Core Challenges 1️⃣ Fragmented Systems & Data Your GTM teams (Marketing, Sales, CS) run on disconnected tools and KPIs making ROI visibility, forecasting and decision-making nearly impossible. 2️⃣ Misaligned Revenue Motions Acquisition, expansion and retention efforts aren’t unified under one growth model. Teams optimise locally instead of scaling globally. 3️⃣ Reactive, Not Predictive GTM Instead of leading with insights and capacity models, GTM teams react to quarterly pressures losing strategic control and operational efficiency. ⚙️ Why It Happens When growth capital arrives, companies often add tools, people and processes faster than they align the core RevOps foundation. The result? Operational debt, inefficiency and lost growth momentum. 💡 The Fix Winning SaaS portfolios treat RevOps as a strategic growth function not a support layer. Here’s how they do it: ✅ Unify GTM data into one source of truth. ✅ Translate growth targets into operational playbooks. ✅ Integrate and automate revenue workflows using AI. ✅ Shift from lagging to leading indicators to forecast scale with precision. When RevOps maturity meets GTM alignment, growth becomes predictable, repeatable and investor-confident. At Corpridge, we help GTM and Revenue leaders enter the new fiscal year with clarity, precision and a scalable growth system; driving predictable revenue, stronger client relationships and a high-performing team culture. 🚀 Ready to uncover what’s blocking your revenue engine? Book a 30-minute RevOps & GTM Strategy Session and start building a scalable operating model for 2026. 👉 https://lnkd.in/e2U2BUdp #Corpridge #RevenueOperations #RevOps #GTMStrategy #SaaS #PrivateEquity #GrowthStrategy #SalesOperations #MarketingOperations #CustomerSuccess #B2BMarketing #B2BSales #GTMAlignment #SaaSScale #PredictableRevenue #RevenueGrowth #OperationalExcellence #SalesEnablement #Automation #AIinSales
2
1 Comment -
RevOps Global
251 followers
Is your Lifecycle Model holding you back? Most RevOps teams think their lifecycle model is “good enough.” But what if it’s hiding the biggest gaps in your funnel? Traditional lifecycle models assume a clean, linear path: Known → MQL → SQL → Opportunity → Closed-Won But that’s not how modern B2B buying works. ✅ A Mature Lifecycle Model Should: 1️⃣ Track non-linear buyer journeys 2️⃣ Support the re-entry of previously lost leads 3️⃣ Capture both inbound and outbound sources 4️⃣ Align Marketing, Sales, and CS around one funnel Here's a quick self-check. Can your model... ☐ Handle leads who re-engage after months of silence? ☐ Show marketing influence for outbound leads? ☐ Track expansion and upsell opportunities? ☐ Reflect multiple touches across departments? If you answered “No” to any of the above... Your lifecycle model is likely underreporting funnel performance. And it's costing you pipeline.
9
1 Comment
Explore collaborative articles
We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.
Explore More