Monte Carlo

💞 💘 💖 💗 You make my heart race faster than a data issue impacting my downstream dashboards. 💞 💘 💖 💗 On this day of love, we gathered some data-themed Valentines for all the data folks in your life. <3 Happy Valentine's Day! #ValentinesDay #data #AI #GenAI #apacheiceberg #spark #SQL

Data teams knew it. Now CIOs are saying it. Data quality is THE problem to solve for enterprise organizations. According to a recent survey from Info-Tech Research Group, data quality and governance shot to number 1 on the list of top priorities for 2025 as part of an generalized effort to democratize access for data and AI. Here’s the snippet from their press release: 1. Distribute Data and AI Access Across the Organization Ensuring high data quality is essential for AI effectiveness. CIOs must implement rigorous data governance frameworks to improve data accuracy and reliability, empowering teams to leverage AI responsibly while preventing data silos and security risks. CIOs are advised to democratize access to data and AI capabilities to foster innovation. Establishing robust data governance and clear AI strategies will empower teams to utilize AI tools responsibly while mitigating risks like data silos and security vulnerabilities. Principal Researcher Brian Jackson said it well— "CIOs have done well to drive digital transformation by rescuing data from organizational silos and building resilient information structures that facilitate productive engagement. Now they need to continue that journey into the age of AI and incorporate emerging technology to their own advantage.” You can’t democratize what you can’t trust. Before any organization can give free access to data and AI resources, they need rigorous tooling and processes in place to protect its integrity. That means leveraging automated and AI-enabled solutions to scale monitoring and resolutions, and measure adherence to standards and SLAs over time. Without those priorities in order, the financial and reputational risks could be catastrophic. Because the only thing worse than one person using bad data…is an entire enterprise using it. Or worse—an unmonitored AI agent, and no humans at all. So…what’s on your priority list this year?

Don't miss our next Serving Data event in Philadelphia next week! Join us and our friends at dbt Labs for dinner, drinks, and data discussion. Plus, you'll hear from Brian Taylor, Lead Technical Product Manager at Nasdaq who will share how his team has been building data and AI trust with the right people, processes, and technologies. 🚀 Register here: https://lnkd.in/ejZw3sxi #phillydataleaders #dataengineerng #dataproducts #dataanalytics

It was an amazing experience talking about Data reliability and it’s impact on AI over a fireside chat with Shane Murray last night in Boston. It was great to connect with other data leaders and discuss their journey in AI and analytics and the problems they are solving. It was great to share the SurveyMonkey Data platform and AI journey and our future acceleration state with the engaging audience. Thank you Sydney Brock Nielsen and Monte Carlo for the opportunity. Thanks Jas Sidhu for great hospitality before and after the event. #dataengineering #ai #dataanalytics

What a fantastic night in Boston at Serving Data with dbt Labs! 👏 Thank you to Sri Subramanian for sharing your insights on ensuring trusted data and AI, and thank you to everyone who joined us! Join us in Philadelphia for the next stop next week: https://lnkd.in/ejZw3sxi #ServingData #dataengineering #dataleaders #dataquality #AI #GenAI

Gartner Data & Analytics Summit in Orlando is right around the corner. Are you ready? ☀️ We've compiled everything you need to know before you go, including can't-miss sessions, happy hours, dinners, and more. Check it out: https://lnkd.in/euthRHjZ Be sure to swing by Booth #219 to say hello to the team and grab some swag! Want to book a meeting? Head here: https://lnkd.in/eu6CXQEB See you there! #GartnerDA #dataobservability #data #AI #dataanalytics

We'll be at the AI in Production Mini Conference at the Amazon Web Services (AWS) GenAI Loft in San Francisco on February 28th! Swing by to say hello, catch some demos, and learn how leading data teams are leveraging data observability to get AI-ready in 2025. 👋 Want to join us? Register here: https://lu.ma/h4ljngpv Yujian Tang OSS4AI #GenAI #AIevents #dataquality #datatrust Learn more about what it takes to get your data AI-ready here: https://lnkd.in/eQg63Wtb

Data engineers are the unsung heroes of the AI revolution. Over the last two years—particularly as large models have gotten better at predictive use cases— there’s been a lot of generalized fear about AI replacing XYZ role. But for data teams—and engineers in particular—it's exactly the opposite. There seems to be an insatiable appetite amongst executives for new GenAI projects. But no matter how much FOMO your CEO is experiencing after watching the latest agent demo, they know that implementing any LLM needs to be done thoughtfully. That all starts with the data team. To deliver meaningful business value, AI models NEED reliable first party data that's been governed for security, privacy, and scalability. And in most organizations, it’s the data engineers who are doing that work. Want to carve out a niche for yourself in the AI economy? Become an expert at AI-readiness. That means developing a system and culture of: - Curating your data to solve real business problems - Managing your data for security and privacy - And most importantly—validating the quality of your data for AI use cases. The best part? If your data is AI-ready, it'll be ready for everything else too. Why? Because what AI needs from your data is exactly the same thing every other data product needs. AI just raises that bar a little higher. But then again, there's always a high bar for heroes.

Today's the day! Join us and dbt Labs for our Serving Data dinner & happy hour in Boston! We'll be serving up drinks, dinner, and discussion about how data teams are readying their organizations for AI with the right people, processes, and technologies. Plus, you'll hear from Sri Subramanian, Director of Data Engineering at SurveyMonkey, who will share his expertise and best practices during a fireside chat! 🚀 See you there! Register here: https://lnkd.in/eDm6HdBk #servingdata #dataevents #dataquality #AI #datatrust

Enterprise data teams are busy enough as it is. Add reactive data quality management to the list, and you're stuck playing catch-up for the long haul. Don't miss our live webinar, Proactive Data Monitoring: Enhancing Enterprise Efficiency with Data Observability, this Thursday at 9am PT! You’ll learn how Monte Carlo enables: 🚀 Proactive anomaly detection to reduce data downtime 🚀 Faster root cause analysis to streamline troubleshooting 🚀 Scalable incident management processes that improve team efficiency 🚀 Increased data pipeline reliability to support expansion 🚀 And more! Register here: https://lnkd.in/d-Q368fJ #dataobservability #datamonitoring #livedemo #datateams