Promethium

Where's your D&A team spending its AI budget? For most: code generation pilots. Clean demo, easy ROI story. Gartner CDAO Survey 2026: AI for analytics delivers 42% business-value lift. Code gen only 27%. → hubs.ly/Q04gQCSS0

Designing agentic analytics? Two decisions you can't conflate: Maturity dimensions (domain scope, system scope, use-case complexity). Design choices (autonomy, action scope, interaction mode) . Most teams treat them as one. The pilot doesn't survive it. → hubs.ly/Q04gQJdR0

New BARC Spotlight from Kevin Petrie: the "agentic analytics fabric" lets analytics agents reach distributed data live and activate the metadata that gives them context. 47% of orgs have AI data in multiple physical locations. The fabric is built for that. hubs.ly/Q04gQGm30

At Gartner D&A EMEA last week, we got the same question on repeat: Context graph vs. knowledge graph vs. data catalog vs. semantic layer — what's the difference, and why does AI need any of them? We wrote the breakdown. → hubs.ly/Q04gQdv70

Watch the full episode: - YouTube: youtu.be/OWKievu0XIE - Spotify: open.spotify.com/episode/7A7omf… - Apple Podcast: podcasts.apple.com/ar/podcast/ep-…

New on The AI Data Fabric Show: Prat Moghe with Andrew Clyne — serial CDO (Comcast, Visa, Expedia, CenturyLink). His take: the CDO role has permanently shifted from protecting the bottom line to driving top-line growth. Prat's takeaways: hubs.ly/Q04h7Rpc0

What's the highest-ROI area for CDAO investment? New Gartner CDAO Agenda Survey 2026: analytics use cases deliver the highest ROI — and have the lowest enterprise penetration. +42% lift, vs. 27% for code generation, where most teams are spending today. → hubs.ly/Q04gQJcY0

"Cars have brakes in order that you can go fast." Kjersten Moody (3x CDO — Unilever, State Farm, Prudential) on why governance isn't friction. It's the frame that lets teams move without asking permission. → hubs.ly/Q04f-9-s0

Plug Claude into your enterprise. Ask a real question. It can't get it right. Data is distributed. Context is fragmented. Intent is inferred. Claude can't solve any of those. Mantra can.

50% of enterprises have AI agents in production. Only 27% use them for analytics. That gap is the whole story. 5 takeaways from our panel with Kevin Petrie (BARC): context engineering, scattered metadata, embedded governance, rewiring the stack. → hubs.ly/Q04f-7mv0

The agents are in your enterprise. The accuracy isn't. It's not a model gap — it's architectural. AI-ready data = right data + right context + right intent. Mantra wires all three for any agent. → hubs.ly/Q04f-4H80

Last call — Gartner D&A EMEA next week, London. A few meeting slots still open at booth 814. Theater session Mon @ 17:35: "Wire Your Agentic Enterprise with AI-Ready Data for Trusted Insights." → hubs.ly/Q04fHm1T0

What was our revenue last quarter?" Sounds simple. It isn't. Different systems. Fiscal vs. calendar. Bookings vs. recognized vs. ARR. The AI doesn't know — so it picks a table and returns a number that looks right but isn't. Better AI = better context. → hubs.ly/Q04fg_qp0

Two different decisions get conflated in every agentic analytics conversation: Maturity = how far you've grown (data, use cases, domains) Architecture = how you've designed (autonomy, action, interaction) More autonomous ≠ more mature. Full framework: hubs.ly/Q04fgCW70

Super-capable AI agents need AI-ready data to deliver trusted insights and make reliable decisions. Our next release of Mantra's AI Insights Fabric to close that architectural gap. Watch ↓ hubs.ly/Q04fw_hP0

"We need a context graph" is the new "we need a data lake." Most of the context your AI needs already exists — it's just fragmented across catalogs, BI, and tribal knowledge. How to start building one without boiling the ocean ↓ hubs.ly/Q04fgMym0

1 week out — Gartner D&A EMEA, London, May 11–13. We're at booth 814 showing how to wire your enterprise for trusted agentic analytics — across cloud, SaaS, and on-prem. Theater session Mon @ 17:35: "Talk to All Your Data for Accurate AI Insights." → hubs.ly/Q04fgHYf0

"You've gone from over 50% 100 years ago to less than 2%. And not half the country is unemployed." Mano Mannoochahr (former CDAIO, Verizon & Travelers) on the AI Data Fabric Show, reframing AI displacement anxiety: hubs.ly/Q04dqKLk0

Knowledge graph, data catalog, context graph — what's the difference? - Knowledge graph: what things are - Data catalog: where things live - Context graph: how decisions work The third is what most AI initiatives are missing. Our full guide: hubs.ly/Q04dqy_f0

AI is only as smart as the layers you've built. Most stop at the semantic layer. AI that actually works needs all five — up through tribal knowledge and decision memory. Our full guide: hubs.ly/Q04dqP_z0