Avo

This week was not just a series of launches (although it has been a blast seeing all of these shiny new updates to Avo finally come to fruition 😍). It has been a massive step towards a bigger vision. Let me explain by putting my “How might we” cap on for a second… - How might we enable data mesh principles for event data quality at scale? - How might we empower data teams to work in lock step with other stakeholders, especially developers and domain owners? - And the biggest one: how might we make it easy, fast, and FUN to create great data fast? We’re just getting started, but what a start! And the best part is that the journey to get here has been the result of incredibly exciting collaboration with our design partners and friends in the data space. So if there’s only one thing you should take away as we look back on what we launched this week.. It’s this: The Avo team is not limited to our team members, but to a wonderful community of awesome, passionate people. It wouldn’t be possible for us to even make a dent in these juicy challenges without you. But our work isn’t done! Please continue to share your insights and feedback to help us solve every “How might we” on our list 🙌 I can’t wait to get started on the next chapter with you all. Let’s go 👏

Over the years, we’ve had incredible enterprises like Delivery Hero, BILL .com, and Condé Nast adopt Avo—and they’ve continued to expand their use over time. It’s been incredibly rewarding for our team to see how Avo has become essential to their data governance efforts 🤩 But at some point, Avo started to feel like it wasn’t quite big enough for these enterprises. I like to think of Avo as an apartment in this context—they started by leasing a room, expanded over time, and eventually took over the whole apartment. But now they’ve brought in the entire extended family and desperately need more space. So, we built Avo Organizations—we turned that apartment into an apartment building! 🏢 An Avo Organization is a collection of independent schema registries (typically associated with the org’s subsidiaries), with the ability to define Centralized Schemas for events that need to be tracked uniformly across all subsidiaries. Huge shoutout to Klara Arnalds, Bragi Bergþórsson, and Björn Jóhannsson for their hard work in building this out to meet the growing needs of our largest customers! 🙌 Learn more about how Organizations and Centralized Schemas can help with federated data governance at scale in the link below ⬇️ What do you think? What do you like about this? Where do you want to see Avo Organizations go next?

Developers hate implementing analytics. Here's why—and how we’re helping you fix it: Analytics implementation is one of those “chores” that usually gets done right before a feature launch. As a developer who's been in this position many times, all I want is to get the feature into users' hands and move onto the next exciting thing. So when I see an analytics ticket that says something like "add an event when people use the feature with some properties, and reuse that other event I can't remember the name of..." (a bit extreme example, but you get the idea 😅), I have two options: 1/ Ship half-baked analytics that add little value, knowing I’ll be asked to fix the tracking later (interrupting my focus), or 2/ Chase down someone who can provide more granular requirements (blocking my release while I wait for answers from busy people) It doesn’t have to be this way. The more accurate the tracking requirements are, the faster developers can get it done. And as a bonus, you get better data in return. That’s why I’m so excited about today’s launch of Event Variants and Event-specific property constraints in Avo! We’re enabling domain experts to define precise, scenario-specific requirements for every event and property—turning analytics implementation into something developers can easily knock out in minutes and get that feature shipped ⛵️ More empowered domain teams, happier developers, and more accurate data => Win-win-win! Big shoutout to Hugi Hlynsson, Svala Hjörleifsdóttir and Aleks Verein for sweating over every detail to make these features seamless for our users! While they might seem simple on the surface, it took a lot of heavy lifting behind the scenes to get right 👏 Learn more about how Event Variants and Event-specific property constraints unlock better data design and implementation in the link below ⬇️ and then: Tell me what you think? What do you like about this? Where do you want to see this go next?

When I was a developer at QuizUp, I used to ship features without even thinking about how they should be tracked. A few weeks later, someone from the data team would come asking, "Where’s the data from that feature you just launched?" My answer? "What data?" 🤦♂️ But that all changed when I learned how powerful product analytics can be for a product builder. Seeing how my features performed, where users got stuck, and what worked well totally changed my approach. Suddenly, we were involving the data team before development even started, defining goals and setting up tracking for new metrics to measure success. As soon as the feature went live, we’d dive into the dashboards in Mixpanel or Amplitude to watch, in real time, how the feature was impacting actual people. My dopamine loop as a developer shifted from merging pull requests to seeing the real-world impact of my work. From then on, we never shipped without ensuring the data was airtight. And who better to define that data than the feature team? We had the full context of the problem we were solving, and that meant better, more relevant data. That’s why we’re so excited to introduce Domains in Avo! With Domains, data teams can empower domain experts to take ownership of their data design, without sacrificing quality. No more bottlenecks, no more data team overload—just better data, faster. Major shoutout to the product team bringing this vision to live Klara Arnalds, Svala Hjörleifsdóttir, Bragi Bergþórsson, Hugi Hlynsson, and the incredible design partners that have worked closely with us to get this right—including Cathy Wong, Coty Pastene, MBA CDMP, Ursula L., Elmira G. and Giorgio Terreni who went the extra mile to give us feedback on the post we’re sharing today 👑 Learn more about Domains in Avo in the link below 👇

“So now Avo does business glossary too uh? We're quickly approaching "now it just needs to make coffee" levels ☕️🚀” – Our good friend Giorgio Terreni, when learning about Avo Guardrails. Confession 🫣: Not once have I made coffee in the Avo office. Why? Because my colleagues are massive nerds who weigh the beans and tweak the grinder and have coffee brewing down to such an art that I don’t feel qualified. 😬 I could make some crappy coffee fast, but the rest of the team would probably find it undrinkable. So often I just hop out for coffee to go or just wait for someone else to make it... Similarly, data teams tend to be the only ones with the know-how to design data that’s up to standard. So they either become a bottleneck or product teams bypass the system and create sub-standard data that compromises long-term data quality. Avo can’t make coffee (yet). But today we are taking a major step towards enabling anyone in the organization to create high-quality data. We hope this release will free data practitioners from being human spellcheckers—and let them spend that time on more meaningful work. A huge thank you to Qiaoran Abbate, Jessica D., and Giorgio Terreni for your invaluable feedback and thoughtful contributions that helped make Guardrails possible. And special thanks to Bragi Bergþórsson who (among others) did incredible work in building this feature, and always makes spectacular coffee ☕️ Dive deeper here: https://lnkd.in/evrvpakr