Nimble Learn @nimblelearn
Experts in delivering analytics and AI solutions built with Microsoft Power BI, Fabric, and Azure. Posts about analytics and AI. Creators of @opendatablend. nimblelearn.com London, England Joined August 2013-
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The real question for AI agents isn't just "Does it work?" It's: Can we trust how we're measuring success? As AI agents move into business-critical workflows, evaluation becomes a governance challenge. Read: microsoft.com/en-us/microsof… #AgenticAI #AIGovernance #CopilotStudio
#AgenticAI maturity isn't achieved through AI alone, it starts with trusted, well-governed data. Whoop's journey shows how investing in #CleanData foundations, semantic models, and scalable architecture enables AI agents to automate routine work: siliconangle.com/2026/06/03/age…
Most organisations don't need more AI pilots. They need a better way to run them at scale. Microsoft's June Foundry updates reflect a shift from experimentation to execution: governance, observability, and operational confidence. devblogs.microsoft.com/foundry/whats-… #MicrosoftFoundry #AI
The latest collaboration between the Government Digital Service & The National Archives reinforces that high-quality #Data, strong governance, skilled people, & the right organisational culture are essential for trusted #AIAdoption: openaccessgovernment.org/is-data-maturi…
In banking, #DataGovernance is no longer just a compliance requirement; it's a strategic business imperative. Strong governance ensures #Data is accurate, secure, and trusted, enabling better risk management & regulatory compliance. Read more: ibm.com/think/topics/d…
#AI is only as trustworthy as the #DataGovernance architecture behind it. Modern organisations need more than policies; they need clear ownership, automated governance, secure access, and trusted data that scales across the business. Read on for more: databricks.com/blog/data-gove…
Collecting more #Data doesn't create a smarter business; having the right data strategy does. As organisations accelerate #AIAdoption, success depends on clean, connected, and well-governed data rather than larger data volumes. Read on for more: exchangewire.com/blog/2026/06/1…
Get your #Data clean before you start #AI. Some of the most valuable AI signals sit in unstructured data like call transcripts, logs, and customer complaints, often ignored because they don’t fit traditional governance frameworks. Read on for more: forbes.com/sites/johnsvio…
#ERPMigration has a habit of looking straightforward on paper and then quietly turning into a full-time identity crisis for your #Data. You’re not just “moving systems”, you’re translating years of messy history & inconsistent formats. Read on for more: techtarget.com/searcherp/feat…
Being a #DataAnalyst sounds simple on paper: take #Data, make insights, support decisions. In reality, it’s a bit like being a translator in a room where everyone speaks SQL here, spreadsheets there, & business context somewhere in between. Read on: cio.com/article/217583…
Most data strategies don’t fail for lack of a plan, but because they’re treated as a finished document instead of a living cycle. The shift is simple: it’s not “write it once,” it’s “run it, learn from it, refine it, repeat.” Find out more: dataversity.net/articles/accel… #DataStrategy
Dashboards could afford latency. AI applications can’t. GPU-accelerated Fabric Data Warehouse brings: • Real-time analytical queries • Scalable concurrency • One platform for operational + analytical workloads Learn more: community.fabric.microsoft.com/t5/Fabric-Upda… #FabricMicrosoft #Data #GPU
AI was “free” while it was experimental. That’s changing. From 6 July, Databricks will charge for Genie usage beyond the free allowance (Genie, Spaces, Code). Learn more: Docs.databricks.com/aws/en/genie/b… #databricks #ai #price
Most users don’t use features they can’t see. Azure Maps now turns selection tools on by default: • Circle / rectangle • Freeform lasso • Distance or travel time No setup required. Less configuration. More exploration. Learn more: learn.microsoft.com/en-gb/power-bi… #data #azure
Most data issues aren’t technical. They’re consistency problems. Power BI’s DAX UDFs (now GA) move the needle: Define logic once → reuse across measures, columns, visuals. Learn more: community.fabric.microsoft.com/t5/Power-BI-Up… #dax #powerbi #consistency
Lineage works, until it crosses a boundary. Visibility drops, confidence follows. Extended lineage for materialised lake views brings it back. Find our more: learn.microsoft.com/en-gb/fabric/d… #DataEngineering #MicrosoftFabric
Most AI platforms solved model access. That wasn’t the hard part. Recent Foundry updates point somewhere else. This is about lifecycle, not models. build → evaluate → govern → deploy Learn more: devblogs.microsoft.com/foundry/whats-… #foundry #build #deploy
#AI teams love to talk about model performance but quietly ignore where the training data ends up. Every pipeline pull, notebook export, & “quick experiment” can multiply #SensitiveData faster than most governance frameworks can track it. Read on: cio.com/article/417188…
#Notebook export controls in #MicrosoftFabric show a shift: notebooks are regulated workspaces, not playgrounds. Biggest data risk isn’t breaches, it’s ‘helpful’ features working outside the fence. Read on for more: community.fabric.microsoft.com/t5/Fabric-Upda…
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