Goodbye, Hours of Chart-Making: Hello, Copilot
Taking a neat table of numbers and turning it into a beautiful, insightful chart can feel like a chore. You know, clicking through menus, tweaking axis labels, and hoping you picked the right type of chart to tell your data’s story. It’s time-consuming, and for many people, it’s a stumbling block on the road to getting real value from their data. What if you could skip all that manual work? What if you could simply talk to your data tool and have it instantly whip up the perfect bar graph, line chart, or scatter plot? It’s a powerful change in how we interact with spreadsheets and data analysis platforms. This blog post will dive into how Copilot can automatically generate charts and graphs, making you a data visualization superhero with almost zero effort. https://dellenny.com/goodbye-hours-of-chart-making-hello-copilot/Stop Guessing Your Guide to Asking Copilot Questions About Your Spreadsheets
Let’s be honest—how many times have you opened an enormous Excel file and instantly felt your brain shut down a little? You know the insights are in there somewhere… the trend that matters, the weird outlier, the formula that will finally make the numbers make sense. But digging them out can feel like you need a data science degree—and two quiet hours with no interruptions. I’ve been there too. I’ve spent more mornings than I’d like to admit wrestling with complex VLOOKUPs or manually sorting through hundreds of comments. Exhausting, right? https://dellenny.com/stop-guessing-your-guide-to-asking-copilot-questions-about-your-spreadsheets/How to Measure ROI from Copilot Deployment
“So, you’ve rolled out Copilot. Now what?” That’s the question every IT leader and business owner asks after the initial excitement fades. Sure, Copilot feels like magic—automating tasks, summarizing meetings, and even drafting emails—but how do you prove it’s more than a shiny new tool? How do you measure its real return on investment (ROI)? Let’s break it down in a way that’s practical, relatable, and yes, human. https://dellenny.com/how-to-measure-roi-from-copilot-deployment/Beyond the Code: Setting Up Alerts for Unusual GitHub Copilot Activity (and Why You Need To)
It’s 3 AM. You’re sound asleep. But somewhere, a developer’s Copilot instance is working overtime, not on a feature, but potentially on a security breach. GitHub Copilot is a game-changer. It’s the closest thing we have to a genuine, tireless code-whisperer, boosting productivity and making the mundane parts of development vanish. But with great power comes great responsibility—and significant new security challenges. When an AI is operating within your codebase, often with the same access as the human developer, it becomes a crucial new endpoint to monitor. Ignoring Copilot security isn’t an option. Its contextual awareness—its superpower—is also its biggest vulnerability. If an attacker gains control of a user’s session or if a vulnerability is exploited (as has happened in the past), Copilot can become an unwitting accomplice in data exfiltration or the silent injection of malicious code. The solution? We need to treat Copilot not just as a developer tool, but as a privileged system user. We need GitHub Copilot alerts for unusual activity. https://dellenny.com/setting-up-alerts-for-unusual-github-copilot-activity/How to Continuously Optimize Data Quality for Better AI Output
If you’re running a modern business, you’re probably already in on the secret: Data is the new oil. But if data is the oil, then Data Quality is the refinery. You wouldn’t put crude, unfiltered oil in a precision-engineered race car engine, right? So why would you feed your cutting-edge Artificial Intelligence (AI) models raw, messy, or incomplete data? The truth is, many organizations treat their data pipeline like a one-off cleanup project. They do a big purge before a new AI initiative, dust their hands off, and expect everything to run perfectly forever. But data—like the real world it represents—is a living, breathing, constantly shifting entity. It degrades. It drifts. New sources introduce new inconsistencies. The old adage “Garbage In, Garbage Out” (GIGO) has never been more relevant than in the age of AI. A model trained on flawed data won’t just give you slightly off results; it can learn and amplify those flaws, leading to biased outcomes, catastrophic business decisions, and a loss of customer trust. The solution isn’t a one-time scrub; it’s a commitment to Continuous Data Quality Optimization. It’s about building a robust, ‘always-on’ system that ensures your AI is running on the cleanest, most reliable fuel possible. https://dellenny.com/continuous-data-quality-optimization-for-ai-the-essential-guide/AI Terms Explained for Microsoft 365 Users
Welcome to the future of work! If your days revolve around Word, Excel, Outlook, and Teams, you’ve probably noticed something huge changing: Artificial Intelligence (AI) isn’t just a sci-fi concept anymore; it’s right there in your Microsoft 365 toolbox. Tools like Microsoft Copilot are weaving AI magic into your everyday tasks, making you more productive than you ever thought possible. But let’s be real. All the talk about LLMs, Prompts, and Generative AI can feel like reading a secret language. It’s a ton of jargon that can make the benefits of AI seem confusing or even intimidating. Don’t sweat it! This blog post is your plain-English guide to the essential AI terms you need to know to truly master the new intelligence baked into your Microsoft 365 apps. Think of it as your translator from Tech-Speak to Human-Speak. By the end of this, you’ll be talking the talk and walking the walk of an AI-powered pro. https://dellenny.com/ai-terms-explained-for-microsoft-365-users/Monitoring Security and Compliance Metrics for Copilot: A Human-Centered Guide
As organizations continue adopting AI-powered tools like Microsoft Copilot, one theme keeps rising to the surface: trust. Companies want to leverage Copilot to boost productivity, streamline workflows, and assist employees in their day-to-day tasks—but not at the expense of security or regulatory compliance. That’s why monitoring security and compliance metrics for Copilot has become just as important as implementing the tool itself. While Microsoft provides strong enterprise-grade protections, every organization still needs observability, governance, and ongoing oversight. In this post, we’ll explore what it really means to monitor Copilot security and compliance metrics in a way that feels approachable, human, and aligned with real-world business needs. Whether you’re an IT admin, a security professional, or simply someone curious about how AI governance works, this guide is for you. https://dellenny.com/monitoring-security-and-compliance-metrics-for-copilot-a-complete-human-focused-guide/Building Copilot Usage Dashboards in Power BI A Complete Guide
As AI tools become essential in everyday workflows, organizations increasingly want to understand how these tools are being used. Microsoft Copilot—now integrated across Microsoft 365—promises improvements in productivity, decision-making, and collaboration. But like any tool, leaders need visibility into its usage: Who’s using Copilot? How often? Which features? Is productivity actually improving? That’s where Power BI comes in. With its ability to connect to Microsoft 365 usage data and transform raw logs into actionable insights, Power BI is the perfect platform for building Copilot usage dashboards. Whether you’re an IT administrator, analyst, or a business stakeholder, creating these dashboards helps you track adoption, spot trends, and measure ROI. In this guide, we’ll walk through everything you need to know—from data sources and modeling tips to the visuals that deliver the most value. https://dellenny.com/building-copilot-usage-dashboards-in-power-bi-a-complete-guide/
