Select Star
@selectstarhq
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Select Star is an automated data catalog, data lineage, and data documentation platform designed for data discovery and data governance.
Joined July 2020
Today marks a big milestone for our team: @Snowflake has announced its plans to acquire the @selectstarhq platform! ⭐❄️🧵
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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:
selectstar.com
I'm excited to share that Snowflake has announced its plans to acquire the Select Star platform. This marks a new chapter in our mission to bring intelligent metadata context to every organization...
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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 👉
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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
selectstar.com
AI in BI tools often fails without context. A semantic data model gives LLMs shared meaning, query accuracy, and business consistency.
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🔍 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
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dbt Coalesce 2025 kicked off with big moves 💥 • dbt + Fivetran → pipelines, models & metadata together • Fusion → Rust-based, multi-engine compiler • MCP + MetricFlow → governed, AI-ready analytics Get the recap:
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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
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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 👉
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🤔 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
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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:
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Drowning in S3, Glue, Redshift tables with no clue what’s actually used? 🤿 AWS stacks get messy fast. Select Star automates metadata management with: ✅ Auto-discovery ✅ Column-level lineage ✅ Usage insights ✅ Native AWS integration 🔗
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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. 📖
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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
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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 👉
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🤔 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:
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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
selectstar.com
Discover how Datasembly cut 90% of data engineering time and saved $30K+ annually in Snowflake costs using Select Star’s data discovery and lineage tools to streamline change management and improve...
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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. 👉
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🤖📊 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:
selectstar.com
Learn how semantic layers turn complex data into trusted insights, enhance AI accuracy, and enable faster, more reliable analytics.
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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 👉
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🚀 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 👉
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