960 actions suggested by AI in 1 day.🤯That's what Connecty AI delivered to a client yesterday — WITHOUT A SINGLE PROMPT.
GOOD: AI has surpassed human capability.
SCARY: who's going to implement 960 actions?
LESSON: AI can surpass humans, but can't bypass them!
Just watched AI-generated UGC video ads outperform human-created ones for the first time. 🤯
One agent watched the videos and sent instructions to another agent for editing. The self-optimization loop.
Super excited to push the boundaries for video ads. https://t.co/yO0zlSCkUE
Stop Building Dashboards No One Uses!
Most companies have 100+ dashboards. Most get checked once, then forgotten.
The problem? Data teams start with “what should we visualize?” instead of “what business GOALS are we supporting?”
Real value happens when you work backward from business goals - not visualization requests.
So before you open your BI tool, ask your business team
1️⃣ What are the top 3 GOALS per department this quarter?
2️⃣ Which north star metrics define success?
3️⃣ What actions do you take based on those numbers?
And then either curate a list of metrics, measures, filters, dimensions that meets those goals and empower data-savvy business teams with self-serve dashboards based on it.
🚀 Or simply generate a fully automated AI-built and AI-governed 'Day Zero Semantic Layer' for FREE today.
🧭 The First 90 Days Playbook for Data Leaders
🗺️ Phase 1 - GOALS BEFORE DASHBOARDS
- Don’t start with dashboards consolidation.
- Sit with each team and list the 2–3 decisions they make weekly (e.g., optimize spend, ship a feature, reduce churn).
- Turn those into goal statements with clear thresholds.
- Even if metrics grow later, you’ll know which numbers must be reliable first.
💡 Pro tip: Use Connecty's DayZero Semantic Layer to pre-populate a comprehensive list of your personalized business goals by each function. https://t.co/wA8s6cT0XW
🗺️ Phase 2 - AI AUTOMATED GOVERNANCE
- Pull together every existing definition - from wikis, dbt models, Google Sheets, SQLs, DAX.
- Highlight conflicts.
- Then host short workshops to align on Revenue, Active User, CAC, Churn, LTV. (Yes, it’s painful but essential.)
💡 Pro tip: Tools like Connecty’s DayZero Semantic Layer can auto-learn base semantics from query history + metadata to make alignment in minutes than weeks. https://t.co/wA8s6cT0XW
🗺️ Phase 3 - DRIFT IS NOT A BUG
- Definitions evolve. Version changes are bound to happen - handle them systematically.
- Create a workflow for definition updates, auto-versioning, and safe downstream rollout.
- Otherwise, business teams will create hidden “Google Sheet layers” of their own truth.
💡 Pro tip: Use Connecty’s Autonomous Semantic Graph for AI powered auto-updated definitions in a trusted living semantic graph, and detect or approve any dependencies downstream. https://t.co/6JeZIZIW2D
By Day 90, you’re NOT judged on architecture. You’re judged on TRUSTED decisions.
🚀Announcement! A few months ago, we blogged about our vision 'The Future of Metrics':
→ Auto-generated Metrics Layer
→ Semantics that evolve with your data
→ Meaning both humans and AI can trust
🚀 Today, we're proud to ship that vision to all our beta clients → 'Day Zero Semantic Layer'.
Day Zero Semantic Layer auto-learns your business logic from your query history, schema metadata and enriched catalog - within minutes!
No YAML. No mapping. No waiting.
✅ Query-ready semantics on Day 0
✅ Verified personalized definitions for humans & AI
✅ Built-in governance and explainability
✅ Works with any data source
Try the Future of Metrics today. https://t.co/kQ7sfrm4vJ
Without an autonomous semantic layer, your data team keeps redefining the same metrics for different teams. The result? Multiple versions of the truth - and everyone ends up chasing different goals.
Choosing the right AI Agent for Data Analytics?
Use this 15-Point Checklist ✅
https://t.co/JIZnIWROSf
Don’t settle for surface-level AI - demand true autonomy.
#AI#DataAnalytics
AI isn’t failing your analytics. Your customized, inconsistent KPI definitions are.
Every team defines “revenue,” “ROI,” “active user” differently.
Marketing has one version, Finance has another, Product has a third-and none of it’s documented.
Then someone asks the data team to 'plug' that new AI data copilot into the data stack and wonders why the answers don’t make sense.
That’s why @ConnectyAI's Chat is powered by a real-time context engine to handle that chaos - the messy prep work no one talks about.
It tracks how metrics evolve across teams, keeps definitions versioned, and resolves conflicts over time - with humans in the loop.
👉 Link in the comments for more info!
#AIAnalytics #AgenticAI #Data #AIData #BusinessArtificialIntelligence
Can AI fix your broken dashboards?
Our new podcast reveals how our Autonomous Semantic Graph fixes inconsistent metrics and replaces manual semantic layers. It's the world's first Agentic AI with business logic intelligence!
🎧 Tune in to Spotify now! https://t.co/c5SXGZuUtd
#AgenticAI #AgenticAnalytics #ConnectyAI #AutonomousSemanticGraph #AgenticSemanticLayer
@TanelPoder High level ok, but @Google's blog skips the hard parts: 1) Currently @GeminiApp consistently confuses intent hierarchy for a multi-layered question. 2) Needs heavy manual effort to explain semantic relationships - and without that it miserably fails to understand large schemas.
@OpenledgerHQ Explainability alone isn't enough - we need 'Actionable Explainability'. To guide humans with what to do next. To enable effective human-AI collab and achieve accuracy. More on our thoughts here: https://t.co/Yovbj8XPHY
Ever ask an AI data copilot a complex analytical question… and get a totally useless answer?
It’s not your fault. Most AI can write SQL—but they don’t understand the question.
@ConnectyAI does. It reasons like a real analyst.
See how it works 👇
#AI#DataAnalytics#AgenticAI
🚀 Our new explainer video shows how @ConnectyAI 's Autonomous Agentic AI turns raw data into real-time insights with human-in-the-loop.
https://t.co/6dISUv8yII