Trility Consulting

We spent last week at FabCon listening to the shift companies are making from data storage toward a platform that understands how their business actually runs. The vision of Proactive Operational Intelligence is aspirational, but the data Microsoft shared was a striking reminder of the reality: while 80% of AI pilots succeed with public data, only 10% do when exposed to the data complexity of an enterprise. For those already working in the platform, the theme is consistent – scaling is often stalled by foundational hurdles. Practical challenges around data ingestion, schema consistency, and semantic modeling remain the primary blockers to the autonomous agents everyone is excited about. The response at FabCon was a suite of features designed to lower these hurdles. Tools like Fabric IQ and Ontologies are intended to define the meaning of data beyond the table level, while the Database Hub aims to provide a single view across fragmented estates. These updates represent an effort to create a “pit of success” where the right architectural choice becomes the easy one. All that said, the transition to an AI-ready infrastructure requires a level of disciplined data hygiene that many environments aren’t yet prepared for. How is your team navigating the gap between the aspirational unified brain and the reality of your current data estate? #MicrosoftFabric #FabCon #DataStrategy #OperationalIntelligence FABCON & SQLCON - The Microsoft Fabric & SQL Community Conferences

Checked the STATS on Wednesday... and yeah, Fabric After Hours was a winner! 🍻 Beyond the keynotes, the best part of #FabCon2026 was simply bringing the community together. We had a blast hosting everyone at STATS Brewpub and getting into what it actually looks like to build in Fabric every day. We’re currently distilling those conversations into some fresh content – sharing what we’ve learned and what it means for your data journey. Keep an eye out for that POV coming soon! Thanks to everyone who made it a night to remember. The #MicrosoftFabric community is one of a kind. #FabCon2026 #MicrosoftFabric #FabricAfterHours #DataStrategy #Trility Brody Deren, Melissa Creger, Ryan Skarin, Gerard Forbes, Claire Damon

How could near-real-time data improve your decision-making? Learn how it helped this client. https://lnkd.in/gRXgyudp

You can’t build a real AI strategy on top of fragmented legacy data. As a Microsoft Fabric Featured Partner, we’ve seen Fabric act as the catalyst for organizations finally ready to move past tech debt and capitalize on their AI ambitions. We’re headed to Atlanta for FABCON & SQLCON - The Microsoft Fabric & SQL Community Conferences to share those lessons from the field. We’re also hosting a private After Hours on Wednesday. We want to keep it small, so we aren't posting the link publicly – but if you'll be on the ground and want to join us, shoot a DM to Melissa Creger, Brody Deren, Gerard Forbes, or Ryan Skarin for the RSVP link. #FabCon #MicrosoftFabricCommunityConference #MicrosoftFabric #AfterHours #HappyHour

As a Microsoft Fabric Featured Partner, we’ve seen firsthand how this platform is helping teams finally unlock data prisons. It’s one of the most efficient ways we’ve seen to build a single source of truth and get your data AI-ready. Our team is headed to #FabCon in Atlanta this month to share what we’ve learned from leading some of the first implementations. Will we see you there? #SQLCon #FabCon #MicrosoftFabric #FabConAtlanta

AI doesn't fix bad processes – it just makes them fail faster. AI is an amplifier. If your engineering foundation is solid, AI makes you a force multiplier. If your processes are brittle, your tests are nonexistent, and your "DevOps" is just a title, AI will tank your environment at record speed. Poor testing will undermine every gain you made in speed. At Trility, we’re helping clients find where their human processes are too weak to support AI speed. If you can’t deliver working, secure code with humans today, adding AI to the mix just means you’ll be staying up later to fix the outages tomorrow. Is your software delivery foundation strong enough to actually handle the speed AI is promising?

The true divide in AI adoption isn't between those who have the tech and those who don't; it’s between those who are stalled by data sprawl and those who find high-value, low-complexity wins today. In this insight, Ryan Skarin and Andrew Dayton, MS highlight how you don't need a multi-million dollar "spread AI on everything" initiative to see a return. By prioritizing a single, measurable, high-impact business outcome, like an LLM trained solely on your FAQ to reduce support volume, you can deliver the ROI necessary to fund your broader AI ambitions. Our Comprehensive Guide to Enterprise AI Adoption moves past the hype to provide a tiered roadmap, ensuring your data is unified and your people are prepared for the shift. https://lnkd.in/gp6PsV8e

Is your AI sharing too much? It’s a common mistake: connecting an AI to your data and assuming it knows what not to say. But without clear guardrails, your AI doesn't distinguish between a public policy and a private payroll file. It wants to be helpful, so it will happily provide the "right" answer to the wrong person – revealing everything from individual salaries to your lowest proprietary deal rates. At Trility, we don't just "plug in" AI. We engineer the architecture to ensure your sensitive data stays behind a deadbolt. We help you balance innovation with zero-trust security so your AI stays productive without becoming a liability. Stop the data leaks before they start: https://lnkd.in/g_K5Aq39

Could you be overspending on the cloud? Many companies are, and the costs often go unnoticed until they’ve racked up thousands, if not millions, in charges. Unexpected cloud costs can quickly undermine a cloud strategy transformation. We helped a client combat this challenge, achieving a realized annualized savings of $780,000 in only four months. Gain control over your cloud environments and ensure investments deliver maximum value. https://lnkd.in/gpM3Z-3z

Stop paying for idle capacity. Your development team doesn't work 24/7 – why does your infrastructure? In 2026, over-provisioning remains one of the largest silent drains on tech budgets. Many engineering teams still run development and staging environments around the clock, even though they're only utilized about 30% of the time. We’re big on repeatability and pragmatism. Implementing ephemeral environments – systems that spin up when needed and vanish when a task is done – can cut development infra costs by up to 80%. It’s not about cutting corners; it's about senior-level engineering that values efficiency as much as performance. What’s the delta between your peak cloud usage and your average usage? That gap is your waste margin.