Power BI and Fabric team ownership in extended engineering models
When an internal BI team already owns Power BI and additional engineers support Fabric development, how do you divide responsibilities? For example, should the extended team own data pipelines and notebooks while the internal team owns semantic models and reports, or is it cleaner to assign ownership by project? We have encountered this at Datatobiz when implementation work moves into ongoing development and support. Thoughts?
I designed an OS-tan mascot for Microsoft PC Manager! (PC Manager-tan)
Hello! I’m a huge fan of Windows 11 and a daily user of Microsoft PC Manager. Since the app is so incredibly light and useful, I thought it would be fun to give it a face. So, I designed an "OS-tan" style mascot character for it: "PC Manager-tan"! I wanted to share my concept art and ideas with the community. Here are some of her design details: [Design Inspiration & Colors]--------------------------------------------------------------------------------------------------------------- Signature Colors: The green and blue color scheme is heavily inspired by the official Microsoft PC Manager logo. Hair Details: She has a blue 'ahoge' (cowlick) and a blue heart hairpin to represent the distinct dots in the app's logo. Outfit: A Full-Body Style energetic cleaning assistant wearing a cozy cable-knit sweater, a green plaid skirt, and round glasses. Slogan: "We'll clean up your PC for you" [Her Equipment & Skills]-------------------------------------------------------------------------------------------------------------------- Digital Broom (Boost): Her main tool. With one click, she aggressively sweeps away unnecessary RAM usage and temporary files. Sandbox Claw Glove (Security): A mechanical claw she uses to safely catch malware and inspect system health. AI Utility Bag: A handy bag filled with all the convenient AI tools she needs to assist the user. I had a lot of fun making this, and I hope you guys like her! What do you think? It would be amazing if the MS dev team actually saw this! 😂How we’re using Microsoft 365 to reduce merchant QBR prep from hours to minutes
Hi Champions, I wanted to share a practical adoption pattern we have been working on for account teams that prepare recurring customer or merchant business reviews. One workflow we kept seeing was quarterly business review prep: an account manager starts with a CSV or TSV export, then manually rebuilds similar scorecards, summaries, PowerPoint slides, and follow-up notes for many accounts. It is important work, but a lot of the prep is repetitive. We built https://marketplace.microsoft.com/en-us/product/WA200010195as a Microsoft 365 agent to explore how much of that workflow can stay inside the tools business users already use. The current workflow is: - Start from a merchant performance export in CSV or TSV format, either from OneDrive or pasted directly in chat. - Generate executive QBR scorecards for one merchant or multiple merchant accounts in a batch. - Include payments-oriented metrics such as transaction volume, authorization rate, top decline reason, chargeback rate, interchange downgrade, and loyalty spend lift. - Create a PowerPoint scorecard for each account. - Organize the run in OneDrive with an index, per-account status, and an optional ZIP bundle. - Draft a follow-up email that the user can review and send from Outlook. The adoption lesson for us has been that Copilot and agents land best when the workflow is narrow, familiar, and already painful. “Prepare this quarter’s account reviews from the export I already have” is much easier for business users to understand than a broad AI promise. I would be interested to hear how other Champions are approaching similar recurring review workflows. Are your teams using Microsoft 365 Copilot or agents for business-review prep, customer success workflows, sales/account planning, or operational reporting? For anyone curious, the app is listed on Microsoft Marketplace here: https://marketplace.microsoft.com/en-us/product/WA200010195.Copilot Chat Adoption Feedback : Model Selection Governance and Prompt Library Reusability ?
Hello, As part of several Microsoft Copilot adoption projects that I am currently leading across different organizations, two questions frequently come up from both users and administrators. The first concerns the ability to lock or enforce a specific model in Copilot Chat for certain use cases. Several customers would like to guide users toward a particular model when working on specific scenarios (Opus for example) that require a certain level of reasoning, behavior, or response quality. To date, I have not found any official documentation or roadmap information indicating whether this capability is planned. The second concerns the Prompt Gallery / Prompt Library. Saved prompts are very useful for starting a conversation, but they do not appear to be reusable directly within an ongoing conversation. In several business scenarios, users would like to chain multiple approved prompts within the same conversation in order to preserve context while applying different working methods, analysis steps, or processes. Are there any planned developments regarding these two topics? The ability to lock or enforce a specific model in Copilot Chat. The ability to use prompts from the Prompt Gallery / Prompt Library during an already active conversation. I have not found any official information on these topics in Microsoft Learn documentation or in the Microsoft 365 roadmap. However, these capabilities seem likely to facilitate user adoption and help standardize usage patterns across organizations.Should CRM Users Be Measured on Data Quality KPIs?
Most Organisations agree that high-quality data is essential for getting value from Dynamics 365. Accurate customer information supports better reporting, improved customer experiences, more reliable forecasting, and increasingly more effective AI-driven insights. Yet many Organisations continue to struggle with incomplete records, duplicate data, missing activities, and inconsistent data entry practices. This raises an interesting question: Should CRM users be measured on data quality KPIs? Consider a situation many Organisations have experienced. A sales team is expected to maintain customer records, update opportunities, and log key customer interactions in Dynamics 365. However, users are primarily measured on revenue, pipeline growth, and sales performance. As a result, CRM updates are often treated as a secondary task. During a quarterly sales review, leadership discovers that several opportunities forecasted as active were closed weeks earlier, while others had not been updated since the previous reporting cycle. Customer records are missing key information, activities have not been logged consistently, and reporting accuracy begins to suffer. The issue is often viewed as a reporting problem, but in reality, it starts with the quality and consistency of the data being maintained in Dynamics 365. To address these challenges, some Organisations introduce data quality metrics such as: Record completeness Duplicate record reduction Activity logging compliance Opportunity update accuracy Customer data validation rates Supporters argue that what gets measured gets managed, and that data quality should be considered part of everyone's responsibility. Others believe that introducing data quality KPIs may create an additional administrative burden, reduce user adoption, and shift focus away from core business objectives. There is also the question of whether users should carry the full responsibility. Modern Dynamics 365 environments include validation rules, duplicate detection, business process flows, Power Automate workflows, and governance frameworks that can help improve data quality. Some Organisations, therefore, argue that technology and governance should do more of the heavy lifting rather than relying solely on user behaviour. From your experience: Should CRM users be measured on data quality KPIs? Have data quality metrics improved CRM adoption or data accuracy in your Organisation? What KPIs have been most effective? Is data quality primarily a user responsibility, or should technology and governance frameworks carry most of the burden? Have you found a balance that improves data quality without creating additional friction for users? I'm interested in hearing how different Organisations balance user accountability, adoption, and data quality within Dynamics 365 environments.
Measuring success in Microsoft 365 & Copilot adoption
As a student Microsoft 365 Champion, I’m starting to notice that successful adoption isn’t just about enabling tools — it’s about how adoption is measured and guided. In my learning, simple analytics (usage trends, engagement patterns, feedback loops) combined with tools like Power BI seem to make a big difference in understanding what’s actually working and where support is needed. I’m curious — for those working on Microsoft 365 or Copilot adoption, what KPIs or signals have you found most useful beyond basic usage counts?Excel Copilot now supports local files (Preview): what this means for everyday users
In the Microsoft 365 Current Channel (Preview), Excel Copilot Chat now supports local Excel files, not just workbooks stored in the cloud. This is a meaningful usability improvement because many users, especially students and early-career professionals, still work primarily with datasets stored locally on their devices. Why this matters for adoption: Users can now interact with Copilot Chat while analysing local Excel files. This reduces friction for offline work, assignments, and exploratory data analysis. It makes Copilot more practical for everyday learning and productivity workflows. For users learning data analysis, reporting, or business intelligence, this update lowers the barrier to using Copilot consistently rather than only in cloud-based scenarios. I am exploring how these preview features can improve real-world adoption and learning experiences, particularly for students and early-career users who work with Excel daily.Helping students adopt Microsoft 365 tools for learning & productivity
Hi everyone, I’m a Microsoft 365 Champion and MSc Data Science student, and I’m currently helping fellow students get started with Microsoft tools such as: • Power BI (data analytics & dashboards) • Microsoft Learn learning paths • Microsoft 365 productivity tools I’m curious: What are the biggest challenges you’ve seen when introducing Power BI or Microsoft Learn to students or early-career professionals? I’d love to learn from your experiences and share what’s worked in an academic environment."Operational Guide for Microsoft 365 Copilot Adoption" (DNS error)
Hello Community, On the official page **Operational Guide for Microsoft 365 Copilot Adoption**: https://www.microsoft.com/en/microsoft-365-copilot/copilot-adoption-guide Also https://www.microsoft.com/fr-fr/microsoft-365-copilot/copilot-adoption-guide the **“Get the guide”** button points to a CDN link that does not resolve and shows the error: **DNS_PROBE_FINISHED_NXDOMAIN** (host: `clouddamcdnprodep.azureedge.net`). Context: - Region: France ; Browsers tested: Edge and Chrome ; Date/time observed: January 12, 2026 at 17:24 CET - Expected: Access to the downloadable PDF/resource associated with the guide Could you please escalate this to the relevant teams (content/CDN) to fix the link for the “Get the guide” button? In the meantime, what are the official download URLs for this guide? (in English or French) Thank you!
