Coalesce.io

AI-generated code is only useful if the people who inherit it can actually read it 🧐. At #SnowflakeSummit, Coalesce Field CTO Douglas Barrett is running a 90-minute hands-on lab where you'll build data pipelines in Coalesce using AI, from natural language transforms to column-level metadata, with a focus on pipelines you can support long after the session ends. Two sessions available: 🔹 June 1 | 1:00PM - 2:30PM PT | DE112 🔹 June 2 | 6:30PM - 8:00PM PT | DE112 Save your seat: https://lnkd.in/gG9y-UCq

Debugging a broken pipeline means jumping between your orchestrator, SQL transforms, and upstream dependencies. This could take hours of manual investigation before you even know where to look. In this Demo Dive, we walk through a real example of using Snowflake Cortex Code to do that work for you. The AI agent traces failures across schemas, queries, and job metadata, surfaces root causes, and proposes fixes. You'll learn how to: 🔹 Triage pipeline failures in seconds, not hours 🔹 Understand which failure modes to automate vs. escalate 🔹 See how it fits into a production-grade workflow Save your spot below ⬇️

Since we joined Coalesce.io, it's been interesting to see how much more you can do when you have access to metadata from transformations and catalog, and not only quality. I just published Part 1 of a three-part series on going from ad-hoc prompts to production playbooks with the Coalesce MCPs (Transform, Catalog and Quality). The framework is based on what I've seen some of our customers at the cutting edge do, but also increasingly what the Coalesce client services team has been building to speed up work for customers. Part 1 covers how MCP tools actually work, how to chain Coalesce MCPs, and three concrete use cases: planning a schema change, root cause analysis on a revenue anomaly, and fixing unowned tier 1 assets in the catalog. https://lnkd.in/eVA8ErrW

How do you cut a 2-month legacy migration down to 2 weeks without breaking governance ⚙️? Security Benefit did it, and their team is telling the full story at #SnowflakeSummit ❄️. Brittany Y. and Sachin B. will walk through how they rebuilt a critical data pipeline on Snowflake and Coalesce, tested transformations in minutes, and scaled governance with RBAC and dynamic masking throughout. 📍 June 2 | 12:00PM | MI103 Save your seat: https://lnkd.in/gG9y-UCq

Some of the most exciting innovation at #SnowflakeSummit? You’ll find it here. 🚀 Our Blue Square partners are bringing fresh ideas across AI, apps, and data: 🤖📊📱 Airbyte, Alation, Ataccama, BlueCloud, Boomi, Capgemini, CDW, Chalk, Coalesce.io, Coastal, Dataiku, Elementum AI, evolv Consulting, Glean, Google Cloud, Hakkōda, an IBM Company, Hightouch, LandingAI, LTIMindtree, Microsoft Azure, NTT DATA, Omni, phData, SAP, Semarchy, SqlDBM and TransUnion. Make time to explore the ecosystem. 🔍 https://bit.ly/4uPDQT2

The race to AI-ready data is on, and we're going full throttle at #SnowflakeSummit 🏁❄️. This June 1-4 in San Francisco, we'll be at Booth 1204, showing how data teams build transformation, governance, and quality together on Snowflake so your AI runs on trusted data before it ever leaves the pipeline. Here's what's waiting for you: 🔹 Hands-on demos covering AI-assisted development, build-time governance, and end-to-end lineage 🔹 A sweepstakes for a 2023 Aprilia RS660 motorcycle at Activation Space 2108 🔹 Bookable 1:1s with our team so you get a real conversation, not a rushed pitch 🔹 Customer sessions, hands-on labs, and more on the conference schedule Check out the full lineup: https://lnkd.in/gG9y-UCq

Scaling data pipelines shouldn't mean inheriting more risk. Most data teams don't lose control during a migration all at once. It happens one workaround at a time ⚙️. Coalesce uses AI to shrink migration tasks from hours to minutes, turning legacy XML, YAML, SQL, and JSON into standardized, maintainable ELT, without splitting your processing or starting from scratch. 🔹 Keep logic in-platform to realize cloud ROI faster 🔹 Consistent, auditable pipelines with standards built in from day one 🔹 AI-ready data from the moment you land in the cloud Scale shouldn't be a risk factor. See how Coalesce handles migration and modernization: https://lnkd.in/gGWYTN_4

Financial services data teams don't get to pause reporting while they modernize infrastructure. The business won't wait 🚫. That's the constraint Coalesce and Snowflake built this demo around. Watch how a complete pipeline moves from legacy SQL Server to Snowflake, transformation and all, without disrupting the risk and performance attribution reporting that depends on it. You'll learn how to: 🔹 Ingest on-prem financial data into Snowflake via OpenFlow, automated and connector-free 🔹 Model and transform at scale in Coalesce with governed pipelines built for analytics and #AI workloads 🔹 Orchestrate via API so downstream reporting stays connected from day one Watch on demand: https://lnkd.in/gpEV2gjK

Compute cost visibility shouldn't require a separate tool 💸. As data pipelines scale across more jobs, nodes, and environments, spend attribution gets harder to track. Most teams piece it together after the fact, if at all. Our upcoming Demo Dive with Mark van der Heijden and Stephen Murphy shows what it looks like when cost monitoring is built directly into how your data platform operates, using Coalesce query tags and Snowflake's native query attribution together. 🔹 Attribute spend to specific pipelines and workloads, not just overall usage 🔹 Track costs across jobs and nodes with a rolling 7-day aggregation model 🔹 Surface optimization opportunities in near real-time 🔹 Connect cost insights to data quality outcomes with Coalesce Quality Register below ⬇️

Even at the Data Innovation Summit in Stockholm, the signal from practitioners was clear: fundamentals are what make AI actually work 🤝. Great to see Mikkel Dengsøe bringing that perspective to the Databases & Data Quality stage 👏.