Scenario basic help please
Hi. I have a spreadsheet which calculates electricity usage and solar input etc. As the price keeps changing I am putting the new prices into the spreadsheet. I was thinking that I could use Scenarios or similar to be able to see what the bill would have been previously. I have looked at the Scenario instructions but I'm not quite sure how to use it (bit rusty in Excel recently). Is there a training video or similar I could watch. Any help gratefully received. Regards BlueyOffice Hours Follow-up: What does your event team look like?
We just wrapped up a MGCI Training and Office Hours session talking about this very topic. (Link to recording will be added when it's ready) How does your team break down roles and responsibilities for your event planning? Tell us in the comments!Join us at Microsoft 365 Copilot Discovery event in Huntsville, AL! - UPDATED LOCATION AND DATES!
The Microsoft 365 Copilot Discovery event in Huntsville, AL features hands-on demos, expert sessions, and real-world use cases showcasing AI-driven productivity, Microsoft Copilot capabilities, and modern workplace innovation. The event takes place on May 19th 2026 in Huntsville, AL.
combine multiple text into single line of text
Hi is there a way to combine all the cells into a single cell (of text) ignoring the duplicates/repeat values. i know concatenate but that function becomes very lengthy as ill have to define every cell into the function individually. is there any other function where i simply select the entire data (like an array) and it can do the required.
Getting started in Excel Labs Custom Modules (missing "publish" step)
First-time poster — please be gentle! Context Excel for Mac I have a large library of LAMBDA formulas and wanted to manage them using Excel Labs In particular, I wanted to organise formulas into custom Modules Issue How to actually activate functions defined in custom Modules in Excel Labs I recently discovered Excel Labs and was very excited to use it to manage and structure a large library of LAMBDA formulas. My goal was straightforward: create custom Modules to organise formulas by purpose, and then use those formulas in the workbook. However, it took several hours of experimentation and debugging — even to get a trivial example like: ABC() = 12 to work when defined in a custom Module. The missing piece (which Copilot, Google searches, and the README all missed) is this: Functions defined in custom Excel Labs Modules are inert until the module is imported into the special Workbook module. Until that import step occurs, functions in custom Modules: do not appear in Excel Labs → Names do not appear in Formulas → Name Manager are not callable from the grid According to Copilot this behaviour is not currently documented, and the UI strongly suggests that custom Modules are “active” by default — which they are not. Working workflow (for others who hit the same issue) This is the workflow that finally made things work for me (possibly sub‑optimal, but reliable): Create and maintain functions in custom modules (e.g. Transformations) Explicitly import the required functions into the Workbook module, e.g.: TransformAtoB = Transformations.TransformAtoB Workbook module now publishes to: Excel Labs → Names Formulas → Name Manager This makes conceptual sense — maintain a large structured library of formulas (or import libraries from GitHub), only activate the formulas required by a particular workbook. But without documentation, it’s very easy to assume custom Modules are active by default. Why I’m posting this When I finally asked Copilot “Why didn’t you say this up front?”, the answer was essentially: This publish step is not documented in the README or the UI, and users are easily led to assume Modules are active by default. So I’m posting here to save others from repeating the same debugging journey. Documentation request It would help enormously if the documentation (README / FAQ) stated explicitly that: Custom Modules are source-only Importing into the Workbook module is the publish step Only the Workbook module is wired to Name Manager and the Excel grid Even a short note would remove a major stumbling block for new users. I’m not a GitHub user, otherwise I would also raise this there — if someone from the community is able to mirror this feedback on GitHub, that would be much appreciated.Explore curated Microsoft Partner Digital Skilling Journeys
Partners like you understand that skilling isn't optional—it's foundational for success in an AI-first market. Keeping up with evolving technologies and capabilities will better position you with the skills needed to succeed in an ever-changing market. Explore Microsoft Partner Digital Skilling Journeys (PDJs), curated presales, sales, and tech skilling experiences designed to enhance your knowledge aligned with partner strategic wins. First-time users may need to register—use your work email credentials to sign up. Curated journeys include: Microsoft Security Copilot Drive Business Transformation with Microsoft Copilot 365 Innovate with Azure AI Platform Drive Windows in the Cloud with Windows 365 Cloud Endpoints Modern Security Operations Data Security for AI Migrate to Azure Drive Business Collaboration and Teamwork with Microsoft Teams Accelerate Data Analytics Journey with Microsoft Fabric Cloud Security These journeys are tailored to your interests, needs, and role within your organization. Select the link relevant to the journey you're interested in, register today on the Skilling Hub using your organizational login, answer a few questions, and you'll receive tech and sales-ready skilling experiences customized to your interests and goals. Register nowSecure AI Workloads in Azure: Join Our Next Azure Decoded Session on April 8th
AI introduces new risks—like prompt injection, data leakage, and model misuse—which means security teams need visibility and guardrails that extend beyond traditional cloud controls. In our next Azure Decoded session, we’ll focus on securing AI workloads in Azure with Microsoft Defender for Cloud. Register now for the Azure Decoded session on April 8th at 12 PM PST. Bringing AI security architecture to life with Azure Decoded In the Lockdown AI workloads with Microsoft Defender for Cloud session, we move from concepts to implementation and show how these protections appear in the platform. We’ll walk through where Microsoft Defender for Cloud fits into an end-to-end AI security strategy—and how discovery, posture management, and runtime protection work together to secure AI workloads built on Azure. You’ll also see how to connect the dots across the workflow—so signals from AI resources, identity, and data controls roll up into actionable recommendations and alerts. Enable and scope the AI workloads protections in Defender for Cloud Use the Data & AI security dashboard to understand coverage and priority risks Review posture findings (CSPM) and translate them into remediation steps Investigate runtime detections (CWP) and see how they map into Microsoft Defender XDR Our goal isn’t theory for theory’s sake. It’s to help you see how AI security shows up in real architecture and real workflows—so you can apply it confidently in your own environment. Who is this session for? We built this session for practitioners who are actively working with AI in Azure, including: Developers building AI applications and agents Security engineers responsible for protecting AI workloads Cloud architects designing enterprise‑ready AI solutions If you’re balancing innovation with security and governance, this session is designed to help you translate AI security concepts into concrete steps in Azure. Before you join: Familiarity with core Azure concepts (subscriptions, resource groups, identity, networking) is helpful. You don’t need to be a machine learning expert—the focus is on securing the cloud resources and workflows that power AI solutions. From AI security concepts to platform protections If you’d like to get the most out of the session, start with the Microsoft Learn module Protect AI workloads with Microsoft Defender for Cloud. It introduces the building blocks of AI workloads in Azure and the security considerations that come with them. In the module, you’ll learn how to: Identify the layers that make up AI workloads in Azure Understand AI-specific risks, including prompt injection, data leakage, and model misuse Use Microsoft Foundry guardrails and observability to monitor and constrain model behavior See how Defender for Cloud, Microsoft Purview, and Microsoft Entra ID work together for defense in depth and governance Think of this as your foundation: it connects AI workload architecture to the controls you’ll configure in Azure, so you can protect inputs and outputs, maintain visibility, and apply governance without slowing delivery. Catch up on the previous Azure Decoded session If you missed the previous Azure Decoded session—or want a refresher—you can watch it on demand on YouTube: ▶️ Watch the previous Azure Decoded session on YouTube It’s a helpful refresher and sets the stage for the April 8 discussion. Turn learning into hands-on skills If you want to move the show, you can do this in your environment. The Microsoft Applied Skills credential, Secure AI Solutions in the Cloud, is a great next step after the Azure Decoded session. You will: Scope and enable protections for AI-related resources and workloads in Azure Validate coverage and prioritize risks using the Data & AI security dashboard Find and remediate posture gaps (CSPM) that increase exposure for AI workloads Investigate runtime detections (CWP) and understand what they mean in the context of AI workload behavior Triage AI-related alerts and incidents in Microsoft Defender XDR and decide on next steps Get started 1️⃣ Register for Azure Decoded: Lock Down AI Workloads with Microsoft Defender for Cloud 2️⃣ Watch the previous Azure Decoded session before April 8th (optional refresher) 3️⃣ Earn the Microsoft Applied Skills: Secure AI Solutions in the Cloud credential to showcase skills. The goal is to leave with something reusable: a practical sequence you can apply to new projects to confirm coverage, reduce posture gaps, and respond quickly when Defender signals suspicious activity tied to AI workloads.
