Deploying Snowflake with DCM Projects: Beyond CI/CD

Managing Snowflake objects just got a major upgrade with DCM Projects, now in public preview. This declarative approach to your data lifecycle allows you to define and deploy a consistent set of definitions reliably across development, staging, and production. By streamlining updates and providing built-in CI/CD workflows, your team can spend less time on coordination and more time building. Learn more 👉🏻 https://bit.ly/4taZKyP

Next time you ask Cortex Code to build a data product for you - ask it to „use DCM“ to define it as a project that you can validate before deployment and keep versioned.

I thought Dynamic Table were awesome when them came out, really reducing the complexity of data flows with declarative statements, but DCM takes this to the level of whole projects!

Went through this new 𝘿𝘾𝙈 𝙋𝙧𝙤𝙟𝙚𝙘𝙩𝙨 feature from 𝐒̲𝐧̲𝐨̲𝐰̲𝐟̲𝐥̲𝐚̲𝐤̲𝐞̲ 👀 It’s basically Snowflake moving towards managing your entire setup as code 🧩 You define the state you want, and Snowflake figures out what needs to change (create, update, or drop). The flow is pretty straightforward: – 𝘋𝘦𝘧𝘪𝘯𝘦 𝘺𝘰𝘶𝘳 𝘰𝘣𝘫𝘦𝘤𝘵𝘴 (𝘵𝘢𝘣𝘭𝘦𝘴, 𝘵𝘢𝘴𝘬𝘴, 𝘴𝘤𝘩𝘦𝘮𝘢𝘴) – 𝘚𝘦𝘵 𝘶𝘱 𝘦𝘯𝘷𝘪𝘳𝘰𝘯𝘮𝘦𝘯𝘵𝘴 (𝘥𝘦𝘷 / 𝘴𝘵𝘢𝘨𝘦 / 𝘱𝘳𝘰𝘥) – 𝘙𝘶𝘯 𝘗𝘓𝘈𝘕 → 𝘴𝘦𝘦 𝘦𝘹𝘢𝘤𝘵𝘭𝘺 𝘸𝘩𝘢𝘵 𝘸𝘪𝘭𝘭 𝘤𝘩𝘢𝘯𝘨𝘦 (𝘯𝘰 𝘪𝘮𝘱𝘢𝘤𝘵 𝘺𝘦𝘵) – 𝘙𝘶𝘯 𝘋𝘌𝘗𝘓𝘖𝘠 → 𝘢𝘱𝘱𝘭𝘺 𝘵𝘩𝘰𝘴𝘦 𝘤𝘩𝘢𝘯𝘨𝘦𝘴 𝗣𝗟𝗔𝗡 𝘀𝘁𝗲𝗽 is probably the most useful part here. You know what’s going to happen before anything actually runs. Also comes with built-in tracking, like a 𝗹𝗶𝗻𝗲𝗮𝗴𝗲 𝗴𝗿𝗮𝗽𝗵 and 𝗱𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁 𝗵𝗶𝘀𝘁𝗼𝗿𝘆 so you can see dependencies and who changed what. There’s also some integration with 𝓒𝓸𝓻𝓽𝓮𝔁 to help generate and validate definitions 🤖 Overall, just feels like a cleaner and more controlled way to manage Snowflake environments. #Snowflake #DataEngineering #DataPlatform #AnalyticsEngineering #DataOps #CI_CD #InfrastructureAsCode

DCM Projects is an incredibly technology, rooted in changes at the deepest levels of Snowflake. It is the best way to declare what you want in Snowflake and we'll ensure it happens, with full transparency, auditing, observability, and guardrails along the way. DCM isn't just available in the UI and CLI, we've also fully integrated it into Cortex Code and it's absolutely magical. Internally we've been saying, "Cortex Code makes Snowflake easy, DCM makes it safe", due to the ANALYZE and PLAN functionality within DCM. ANALYZE validates the code that you or CoCo writes, and PLAN validates the deployed delta against your environment _before_ you deploy it. The loop between CoCo authoring and DCM's validations are a perfect match. Enjoy using this. We have a ton of new features and improvements coming.

𝗦𝗻𝗼𝘄𝗳𝗹𝗮𝗸𝗲 𝗷𝘂𝘀𝘁 𝗺𝗮𝗱𝗲 𝗶𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲-𝗮𝘀-𝗰𝗼𝗱𝗲 𝗮 𝗳𝗶𝗿𝘀𝘁-𝗰𝗹𝗮𝘀𝘀 𝗰𝗶𝘁𝗶𝘇𝗲𝗻 𝗳𝗼𝗿 𝗱𝗮𝘁𝗮 𝘁𝗲𝗮𝗺𝘀. DCM Projects is now in public preview, and it changes how teams manage Snowflake objects at scale. Instead of scattered scripts and manual deployments, you get a declarative, auditable approach where your database objects are defined in code, version-controlled, and deployed consistently across environments. A few things worth noting here. Auto-dependency resolution means you stop worrying about deployment order. Native CI/CD integration means your data pipelines follow the same engineering rigor as application code. And the Snowflake CLI integration keeps everything in one streamlined workflow. For data engineering teams that have been managing Snowflake manually or stitching together homegrown deployment scripts, this is a meaningful shift. It brings the discipline of software development into data infrastructure without adding unnecessary complexity. If your team is still deploying Snowflake objects by hand, this is worth a serious look. Read the full article here: https://lnkd.in/ghQ6hXxQ #Snowflake #DataEngineering #InfrastructureAsCode #CICD #DataOps

🚀 Snowflake DCM Projects is now in Public Preview — and we’re closing the quarter with serious momentum. In just a few weeks, we’ve seen DCM Projects go from early preview to real-world adoption, with customers actively using it to manage Snowflake infrastructure as code and ship data projects faster. We’ve also added support for SQL procedures, alerts, external stages, file formats, sequences plus UX upgrades in Snowsight / Workspaces to make projects easier to build and ship. If you want a more auditable, scalable way to define and deploy your Snowflake objects as code, check out the announcement + demo and start exploring the Public Preview https://lnkd.in/diDwv2AC Huge kudos to everyone involved in getting us here — big milestone, and just the beginning. 🙌 #Snowflake #DCMProjects #DataEngineering #DevEx #CICD

Snowflake pipelines are often a Frankenstein of components cobbled together—CDC tool, message queue, custom ingestion script—and each one assumes a fixed schema. When your source team renames a column or changes a data type, every layer has to be updated manually and in sequence. The ingestion job still expects the old structure, so incorrect data lands in Snowflake before anyone catches it. By then, your finance team is reconciling numbers that don't add up and the data team is doing emergency backfills instead of building. The technical problem becomes an opportunity cost for your business. Learn how Estuary handles Snowflake schema evolution at scale: https://bit.ly/4tvbAow

We're announcing our integration with Snowflake, leveraging their Connected Application framework to strengthen how enterprise data connects to planning and decision processes. The o9 Connected Application for Snowflake will allow large, complex organizations to break down data silos and run AI-powered planning models directly against a single, governed source of truth across supply chain, commercial, and financial domains. Rather than relying on fragmented point-to-point integrations, the o9 Connected Application supports continuous data flows between Snowflake and o9. 🔗 Read our full press release here: https://okt.to/NpKyU0 #o9solutions #Snowflake #decisionintelligence #PlanningTransformation

𝗠𝗮𝗻𝗮𝗴𝗶𝗻𝗴 𝗦𝗻𝗼𝘄𝗳𝗹𝗮𝗸𝗲 𝗶𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 𝗰𝗵𝗮𝗻𝗴𝗲𝘀 𝘀𝗵𝗼𝘂𝗹𝗱𝗻'𝘁 𝗿𝗲𝗾𝘂𝗶𝗿𝗲 𝗴𝘂𝗲𝘀𝘀𝘄𝗼𝗿𝗸. For too long, data engineers have been manually crafting ALTER TABLE statements and hoping nothing breaks in production. That approach doesn't scale, and it introduces risk at every deployment. Snowflake's DCM Projects change that. With the Cortex Code DCM skill, teams can now scaffold, test, and deploy declarative pipeline changes in a structured, repeatable way. Think infrastructure-as-code principles applied directly to your Snowflake environment — no more ad hoc schema wrangling. This matters most for enterprise teams managing complex, multi-environment pipelines where consistency and auditability are non-negotiable. When your data infrastructure is declarative, your deployments become predictable. And when deployments are predictable, your teams move faster with fewer incidents. If you're building or maintaining data pipelines on Snowflake, this is worth understanding now before your next deployment cycle. Read the full article here: https://lnkd.in/gikK_kj9 #Snowflake #DataEngineering #DeclarativePipelines #CortexAI #DataInfrastructure