Big news: Snowflake plans to acquire the Select Star platform ❄️✨
Helping data teams understand their data has always been our mission. With Snowflake, we’re excited to scale that even further.
Thank you to our customers, partners & community. Read more: https://t.co/jSYzYY1a4j
Still chasing what a column means even as AI “understands” your data stack?
More context = smarter teams & AI. Read our guide on how to:
🧠 Capture meaning, remove silos
⚙️ Build docs into workflows
🤖 Keep them fresh with AI
👉 https://t.co/kRdAK3qTZw
If AI can write SQL, why do its answers still differ from your BI dashboards?
Because LLMs don’t know your metric definitions or join rules.
A semantic data model fixes that 👇
https://t.co/Rj4lOz3Y7U https://t.co/GWouiqxS0g
🔍 What if your data team could find answers in minutes, not hours?
That’s what global manufacturer Samtec achieved with Select Star:
⚡ 95% faster impact analysis
🔍 90% reduction in data discovery bottlenecks
https://t.co/Qy9zryEHwk
Food, drinks & hot takes... how else would you kick off #dbtCoalesce?
Swing by booth 120 to see how Select Star helps teams:
🧠 Automate semantic model generation
📚 Make data findable with a smarter catalog
🔍 Trace end-to-end lineage
📊 Surface what matters with usage insights
AI hallucinating again? 👀
Your semantic layer might be to blame.
See how data teams are fixing it at #dbtCoalesce:
🎤 Catch Alec Bialosky’s talk on Tues @ 11am
💡 Live demos at Select Star's booth #120
👉 https://t.co/7TwZ9Tmkcz
🤔 What if business users could answer their own data questions?
Puntos Colombia used Select Star to turn ticket-driven analytics into self-service.
📚 100% docs centralized
👥 80+ users empowered
🎯 Data team focused on strategy
https://t.co/wGKBvBPTNP
How do you keep dbt Docs fresh as models ship?
🧭 Source: dbt, catalog, or hybrid.
📝 Draft centrally: owners, small edits, reviews.
🔄 Publish once → propagate everywhere.
📊 Surface defs in BI, lineage, search, and more.
Guide: https://t.co/XeU4i3C3sz
If you asked five dashboards for “active customer,” would you get one answer or five? 👀
Open Semantic Interchange (OSI) make semantics portable BI→AI. Select Star turns trusted BI into AI-ready semantics.
📖 https://t.co/GRjvGXoHiV
Does your data stack ever feel like IKEA furniture without the instructions? 🛠️
That’s metadata without proper management: confusing, incomplete, missing a few screws.
Here’s a quick guide to the top metadata tools and what to look for:
https://t.co/59Pph6e00S
Three dashboards. Three numbers. One metric. 🔍📊
The issue isn’t the math. It’s the lineage.
See how Select Star brings column-level lineage to Redshift 👉 https://t.co/byeL3wxLUS
🤔 What’s more valuable than data itself? Metadata.
It shows what data is, where it came from, how it’s used, who owns it, and if you can trust it.
Shinji Kim breaks it down on Software Engineering Daily: https://t.co/254wDjIrUU
What if your next data hire was a platform? 🤖
Datasembly cut project time by 90% and saved $30K/year. Not by hiring, but by getting clear on their data with Select Star.
📖 https://t.co/tZjrf3gjv6 https://t.co/e5Nn8pbfn5
AI struggles with your data not because it’s undocumented,
but because it lacks context.
customer_id isn’t just a string. It’s a relationship, a driver, a business concept.
Context engineering bridges that gap.
👉 https://t.co/W3TjrMiSx6
🤖📊 AI is replacing dashboards but without a bulletproof semantic layer, it’s just guessing.
Trusted definitions, lineage, and context aren’t optional.
Tobias Macey & Shinji Kim break it down on the Data Engineering Podcast: https://t.co/PvaNk3XEBh
How many hours have you lost chasing the real source of a number? ⏳
Table-level lineage is helpful.
Column-level lineage? That’s where the magic happens. ✨
Check out our real-world examples 👉 https://t.co/6FRANkXL64
🚀 Select Star now integrates with Salesforce CRM Analytics!
Search all assets, see full data context, and auto-document recipes, datasets, lenses, and dashboards so your team can trust every metric.
Read more 👉 https://t.co/r7EyVhaneJ