Rupert

Rupert’s no-code monitoring and alerting solution for Snowflake/BigQuery is now available for anyone to try! The free tier doesn’t require a CC and never expires! Couldn’t be simpler to get started.   If you’ve ever felt like there should be a simpler way to:   …be on the “front foot” when it comes to important changes in your data …catch every valuable issue or opportunity in your data warehouse …monitor and alert on important business metrics and events …push actionable data to Slack Then come on down! You’re in the right place 😎 Anyone can get started with Rupert in minutes, completely self-serve. 1. Open a new account at hirupert dot com 2. Connect to your data warehouse (without the overhead of BI dashboards!) 3. Start monitoring the metric or events you care about (Not ready to connect a source? Experiment with our demo data set and example alerts) Once you’ve started your Rupert account, here’s some of what you’ll find waiting for you: AI Assisted, only when you need it Not sure where to get started with your alert trigger criteria? Pattern aware-anomaly detection will catch any unexpected drops or spikes. Not sure how to explain the alert in your message? Our AI-assist will generate a complete message, breaking down the results of your trigger, to get your started. No SQL, code, or engineering is ever required Monitoring anything in your data warehouse and send beautiful alerts to Slack, without being a developer. — We’re also launching today on Product Hunt today 🚀🚀  We’d love your support there too. Link in comments.

Looking to connect with like minded RevOps folks — but w/o the pressure of holding an hors d'oeuvres plate and a drink while attempting to work a room?! 😅 Then come join the Rupert team (Ziv Wangenheim + Reut Vilek) the night before #RevOpsAF kicks off in San Diego! We’re starting the week with a casual dinner at Las Hadas Bar and Grill, right after event registration ends. 📅 Date: Tuesday, May 28, 2024 🕒 Time: 7:15 PM 📍 Venue: Las Hadas Bar and Grill, San Diego (and a big shoutout to Matthew Volm and RevOps Co-op for putting on #RevOpsAF 💪) Limited to 12 spots, so RSVP now to secure your seat! 🚀 https://lnkd.in/eSP4uxsJ

Messy low-level data in Postgres? No issues or aggregations here! 😉 Connect Rupert directly to Postgres. Set up monitoring and alerting for new errors or edge cases (or literally anything 🤯) in minutes. Need to watch *very* closely? No problem. Rupert will check for new results on an hourly basis - and push them directly to the right team member in Slack! #postgres #monitoring #alerting

Have you heard about hashtag #RevOpsAF? It’s the first conference created by, for, and all about hashtag #RevOps pros, and we're pumped to be there in two weeks! If you're planning to be there, stop by our booth and say hi! We'll be discussing and demoing all things PLG/PLS, signals from customer and product usage data, & playbooks that drive revenue 😎 Plus, the sessions should be outstanding! You’ll learn from thought leaders in the operations space like Jeff Ignacio Ali Rastiello, 🐰 Jen Igartua, and Manny Medina to name just a few (and a big shoutout to Matthew Volm and RevOps Co-op for spearheading the event 💪) Want to join us in sunny San Diego? Use RAFRupert24 for 10% off 😉 See you there! #revops #revenueoperations #salesops #salesoperations #marketingops #mops #marketingoperations #conferenceseason

"I'm so tired from herding cats..." I hear it a lot when clients and prospect describe their data operations. And it's completely understood. It's practically impossible to stay on top of everything. Data moves and changes too fast. And you don’t have eyes in the back of your head. And when you miss valuable, actionable insights, it can cost you big time. So that's when I heard about Rupert! I met Ziv Wangenheim., together with Reut Vilek, the mastermind behind this innovative approach to data monitoring, who explained it to me like this: Rupert is like having an always-on watchdog tracking your business data (product usage, telemetry, third party, etc). It monitors the metrics and events closely and sends you alerts if anything needs your attention. With Rupert, you’ll see and take advantage of every opportunity in your data. Picture this: 🌄you're just starting your day, enjoying your morning coffee, when your phone lights up with a message from Rupert. One of your most valuable clients hasn’t logged into your platform for more than three weeks! But with Rupert's timely heads-up, you can jump in, invest some extra TLC, and get that client back on track. Crisis averted! And basically, it can do the same thing in any data domain - * Churn Prevention * New User Activation * Expansion Acceleration * Fraud Detection * Marketing Campaign Optimization * Sales Pipeline Management * Product Development Insights * Operational Efficiency And the best part about Rupert? 🧠You don't need a Ph.D. in data science to use it: The platform has a no-code approach. So, if you're tired of feeling like you're constantly playing catch-up with your business data, give Rupert a shot by taking advantage of their freemium at hirupert.com or by talking with us. However, here is a small disclaimer: ❗you should already have a DWH (data warehouse for those who are not data geeks) in place to enjoy Rupert to the fullest. Not sure how to set up the DWH? Contact me or the team at BIyond - BI, Big Data and Analytics, and we will happily help you make the necessary adjustments and setup.

😿 Sadly, anomaly detection is not one size fits all. That's why Rupert's metric anomaly detection is now configurable! 🎛 Why is this a big deal? Monitoring metrics without anomaly detection is hard. Unless you already have specific, well-understood thresholds to use in your monitoring, writing trigger criteria logic is more art than science. Should you monitor for period over period spikes and dips, and by how much? 10, 15, or 25%? Should you monitor a metric against a moving average of 7 or 14 days? Anomaly detection is a great choice when you don't have this intuition for your metrics yet. Any variation that the model views as an outlier (in either direction) will trigger an alert. But it's hard for a single anomaly detection model to work equally well on *all metrics* Enter, configurable anomaly detection. Fine-tuning of the model lets you: - adjust sensitivity of the allowed results range - include of exclude recent metric data points - Increase/decrease tend flexibility - specify what type of seasonality you expect in your metric Visit hirupert dot com to sign up and try it out for yourself 🚀

Once you've told Rupert what signals to monitor for....why should you need to type them out again in message? With our AI-assisted message content creator, you don't need to! (And if you don't love the word exact word choice, no problem. Editing is still much faster than writing from scratch) Come try it out for yourself! Rupert's free-forever plan includes a ready to use demo asset so you can start exploring: https://www.hirupert.com/

Staying on top of actionable events or signals in your customer and product usage data? It couldn't be easier in Rupert. No complex set up. No queries to write. Just actionable data when and where you need it.

Come hang out after PLGTM in SF today! Sign up here: https://lnkd.in/eVFyM3R9

When you monitor a metric, it's almost never one single metric you care about. You want to track a metric split across a dimension. Regions, accounts, campaign type, etc. Whatever categorical dimension you care about, breakdown your metric monitors across that field. The upshot? Build once, monitor hundreds of geographies or thousands of accounts. Now, should one account or customer success manager get alerts for 1000s of accounts? Next time we'll talk personalization 😎