Marketing Campaign Performance Dashboard
Marketing Campaign Performance Dashboard - Built for Growth & ROI-Centric Teams A well-designed marketing campaign dashboard turns complex marketing data into clear, actionable insight. By consolidating key metrics such as sales, profit, ad spend, ROAS, CTR, CPC, impressions, clicks, and conversions into a single view, it enables faster and more confident decision-making. The report reveals: • Centralized visibility: Consolidates sales, profit, ad spend, ROAS, CTR, CPC, impressions, clicks, and conversions into one unified view. • Performance accountability: Makes it easy to assess which campaigns and channels are driving value versus consuming budget. • Faster decision-making: Eliminates manual reporting and enables near real-time performance monitoring. • Executive-ready insights: Presents high-level KPIs alongside supporting trends and breakdowns for deeper analysis. What makes this dashboard high-impact? This dashboard provides end-to-end visibility across channels, campaigns, devices, and locations, helping teams quickly identify what’s working, what’s not, and where budgets should be optimized. Interactive filters and trend analysis allow users to move seamlessly from high-level KPIs to detailed performance drivers without manual reporting. Ultimately, it supports smarter budget allocation, improved campaign efficiency, and stronger alignment between marketing, finance, and leadership — transforming data into decisions, not just reports. Thank you,
The Book of a Paper Trader: 355 trades, one honest question. Is there an edge?
ALPACA · PAPER ACCOUNT · 27 AUG – 30 OCT 2026 Most trading dashboards show you a P&L number and stop. This report keeps asking why. Over ten weeks an automated bot won +$23,859, and still closed the book at ▼ −$4,711. The story is about where that money went, which part of the system actually works, and what is sitting on the desk right now. Profit factor 0.84 · win rate 50.1% · expectancy ▼ −$13.27 per trade · account equity $95,819 The story in five pages Cover · What am I looking at? Three headline numbers, one candle per trading day, and a “how to read” strip for R-multiple, profit factor and why PAPER matters. The Book · Is the account growing? No. Stop exits alone erase 54% of all gains. September was the bleed (▼ −$6,828), October stopped it (▼ −$13). Only crypto pays (▲ +$631, PF 1.14). The Edge · Where do wins and losses come from? Shorts carry the book: ▲ +$4,727 at 62% win vs longs ▼ −$9,438 at 44%. 40 trades slipped past −1R (▼ −$8.2K), while trailing stops made ▲ +$2,845 at 81% win. The Desk · What is open right now? 74% of equity sits in cash ($71.3K). One name (KO) is 39% of exposure. 631 orders: 43.9% filled, 52% cancelled by design. The Ledger · Let me explore it myself. Every strategy by asset class with trades, a net P&L heat bar, win rate, avg R, profit factor and an EDGE / WATCH / CUT verdict. Storytelling choices Titles state the finding, not the chart type. “From $23.9K won to $4.7K lost”, “Shorts carry the book”, “One name carries the gain”. Every title is a DAX measure, so it rewrites itself when the data changes. One question per page, in the order a trader would ask it: am I growing → why → what is at risk now → let me dig. Honest framing. A PAPER badge on every page, the 15 crypto pairs with no price data are called out instead of hidden, and the cover explains every metric before you see it. Markers inside the chart instead of legends: PEAK / LOW chips on the equity curve, a win-rate chip on every strategy, “+N smaller” for treemap tiles too small to label. How it is built Microsoft Fabric end to end. Notebooks pull Alpaca (paper) and Binance data into a lakehouse and move it bronze → silver → gold as Delta tables. Two semantic models. A Direct Lake model for daily work, plus an Import copy for Publish to web (Direct Lake can't be published publicly). 146 DAX measures, zero custom visuals. Every chart (equity curve with drawdown, waterfall, lollipop, R-multiple dot plot, treemap, order-flow sankey, cover candles) is drawn in DAX as SVG or HTML. It is fully data-driven and loads as plain images. One design system. A single token set (colour, type scale, radius, 8px spacing) generates the DAX, a tokens.css file and the Power BI theme JSON, so native and custom visuals look identical. Serif display titles, sans labels, tabular figures. Navigation and accessibility. A dark rail with an active pill, made clickable by an invisible vertical Page navigator. Gain/loss colours pass WCAG AA, ▲▼ arrows mean colour is never the only signal, and alt-text measures are written for the main visuals. Explore ▶ Live report: embedded above (start on the cover and use the left rail) ↗ GitHub (notebooks, all DAX measures, theme and design tokens): github.com/PatricRc/trading-analytics-fabric ↗ LinkedIn: linkedin.com/in/patriciorioscanepa · Portfolio: data-pat-ai.netlify.app Paper trading only. Simulated fills, no real money, not financial advice. Built by Patricio Rios with Microsoft Fabric + Power BI.HR Workforce Analytics Dashboard | DataFlip
Managing people data across different systems can make it difficult to understand employee trends, retention risks, and workforce performance. Without clear insights, HR teams often react to problems after they impact productivity and engagement. This dashboard brings workforce data into one clear view, helping leaders make smarter people decisions. Business Impact This dashboard helps organizations: Track employee attrition, retention, and workforce trends Analyze engagement, satisfaction, and work-life balance insights Identify departments with retention risks and performance gaps Monitor training effectiveness and employee development Understand workforce demographics and composition Create dynamic HR insights to support better decisions It helps HR teams improve retention, strengthen workforce planning, and build a more engaged workforce. Who Can Use This Template HR Directors CHROs and HR Executives HR Business Partners People Analytics Teams Talent Management Leaders Learning & Development Teams Workforce Planning Teams HR Consultants and Advisory Firms Discover more insight-driven templates built for real business decisions. Visit DataFlip eyJrIjoiYjhmZGM3MjAtNmJjZS00OWM2LWE4OWMtYzliYWM5MjkwZmY0IiwidCI6ImE5NDUyNTg2LTJmNGMtNGNiMS04ZDJlLTI2ODkyODllZTcyNiIsImMiOjl9IPL Analysis - The Criclytics
Check the latest Dashboard on it with dataset till 2017 at http://bit.ly/iplrmi18. Old Message. Hi All, Just to let you know one of the biggest Cricket League is going on in India and it has started from 5th April 2017. The Name of this league is IPL (Indian Premier League). I have designed a Dashboard which shows the performance of any batsman who played in IPL and also does the analysis of the Match between any 2 teams playing against each other based on the factors like which location is the match, winning percentage of any team who wins the toss and chooses to Bat or Bowling. Have a look how your favourite team is going to perform this IPL. Fixture for the IPL 2017 can be easily found on the internet. The 3rd and 5th Dashboard will just blow your mind. Thanks and Regards, Rohit Binnani. [email protected] Disclaimer: Click Here eyJrIjoiNGEzMzVjNjAtNmQyZi00ZDQxLWJjZDAtNmU4N2VhYTllZjY5IiwidCI6IjRhMjE0MWFjLTQ2NDktNDQ5NS1hZmMzLWU5NjM5NWRkZjU5NSIsImMiOjEwfQUS Housing Market at a Glance: a Power BI report on FRED data
Hi everyone, I built a Power BI report that answers one question: why does housing feel so unaffordable, even when prices look steady? It connects home prices, mortgage rates, income and supply on a single page, using data from the Federal Reserve Economic Data (FRED) API. What’s on the page Six KPI cards: home price index, 30-year mortgage rate, estimated monthly payment, housing starts, new-home supply and rent inflation A key-insight sentence built with DAX, so it updates with each refresh Home prices vs mortgage rate, shown together to explain the affordability squeeze An affordability gauge: estimated annual mortgage payment as a share of median household income, against a 30% guide Starts vs permits, active listings vs new-home supply, and rent vs buy (indexed to 100 at the start of the selected range) A metro snapshot of six Case-Shiller metros with latest index, one-year change and five-year change A 1Y / 5Y / 10Y / Max range selector How it’s built Data comes straight from the FRED API through Power Query. One reusable function (fnFRED) takes a series ID and returns a clean table, and the API key sits in a single parameter. A shared date table connects the series, which update on different schedules (weekly, monthly, quarterly and annual). The range selector is a disconnected table with measures that blank out dates outside the chosen range. The payment estimate uses the median sales price, a 20% down payment, a 30-year fixed loan at the latest weekly rate, and principal and interest only. The project was built as a PBIP, so the model and report are plain text and easy to version. Free to download The PBIX is free. Email [email protected] and I’ll send it. The file includes a working FRED API key, or you can swap in your own free key by editing one parameter. More on my site I wrote a longer walkthrough of each chart, the FRED series behind it and how the payment is estimated. You’ll also find the full report there, plus my other dashboards: https://www.docynx.com/dashboard/us-housing-market-at-a-glance-dashboard I’d like feedback on three things. Is the affordability gauge a fair way to show the story? Which other indicators would you add? And would you prefer a second page for city drill-downs? Thanks for looking! Other links: Free Sample Data Generator • Create Realistic Mock Data Instantly Free XML Sitemap Generator Online – Advanced SEO Sitemap Tool Convert Image to Base64 Text Online Free For PowerBI Image embedding without Storing image on Server | PNG, JPG to Base64 Encoder Compress PDF Documents Online Explore Dashboard GalleryLogistics Management Dashboard
Why is Logistics Management Important? In today’s business environment, logistics is not just about moving goods from one location to another. It involves managing cost, transportation, delivery performance, shipment visibility, and operational efficiency. A Logistics Management solution helps businesses answer important questions: 🚚 Which transportation mode is being used — Road, Sea, or Air? 📦 How many shipments are completed, pending, or delayed? 💰 Where are transportation and logistics costs increasing? ⏱️ Are deliveries being completed on time? 🌍 Which routes or regions require attention? 📊 How is overall logistics performance changing over time? Who Benefits? Logistics teams, supply chain managers, operations teams, finance teams, and management can use these insights to monitor performance, identify inefficiencies, control costs, and make data-driven decisions. I built this Logistics Management Dashboard in Power BI to bring key logistics information into a single view, covering Overview, Road Transport, Sea Transport, Air Transport, and Transaction Reports. The objective is simple: Turn logistics data into visibility, and visibility into better decisions. Thank you.
Fabric Arcade – six retro games (and an emulator lounge) running inside Microsoft Fabric
Hi everyone! 👋 I wanted to see how far a Fabric App could go beyond dashboards, so I built Fabric Arcade: a small arcade with classic-style games you can play right inside the Fabric portal. Single-player runs post to a shared leaderboard for everyone in the workspace. 🕹️ What's in the arcade Bolt Rush – a high-speed platformer with slopes, springs, boost pads and a charge dash, starring an original mascot. Steel Raid – a '90s-style run-and-gun mission. You free prisoners to get heavy weapons and grenades, and the mission ends with a boss tank. Bug Invasion – a fixed shooter against a marching alien fleet that speeds up as it thins out, with bunkers that crumble and a bonus mystery ship. Snake – the classic, with a leaderboard. Snake Versus – two snakes on one board; the last one moving wins the round. Duel Cup – head-to-head football on one keyboard, or against the CPU. All graphics are drawn in code (Canvas and SVG) and every sound is synthesized with WebAudio, so the app ships no third-party art or audio. 🏆 Shared leaderboard Every finished single-player run is saved as a Score row through the Rayfin data API. Row-level security means everyone in the workspace can read every score, but you can only create or delete your own. The ownership check runs server side against your sign-in, so nobody can post a score under someone else's name. 💾 Emulator lounge There's also a corner for Game Boy Advance and PlayStation games, powered by the open-source EmulatorJS. You load a game file you own from your own disk. It's read locally in the browser and never uploaded, and the app itself contains no emulator code, BIOS files or games. 🌐 Coming next: online multiplayer I'm working on online play for Duel Cup and Snake Versus. One player creates a room and gets a 4-character code, and the other joins with it. The Fabric data API is only used for the initial WebRTC handshake. After that, the two browsers talk to each other directly, peer to peer, with the host running the match and streaming its state about 60 times a second. 🛠️ How it's built Fabric Apps (preview) with the Rayfin SDK: authentication, the data API on MSSQL, and static hosting. React, TypeScript, Vite and Tailwind. Each game engine is a pure TypeScript module with unit tests. The canvas components only handle input, drawing and sound. Deployed with npx rayfin up. 🔗 Source code GitHub: https://github.com/Al3ssi03/fabric-games I'd love feedback, especially from anyone else pushing Fabric Apps in unusual directions.Exoplanet Explorer: A little perspective on a very big universe
How does our solar system compare with the thousands of worlds discovered beyond it? I built Exoplanet Explorer to make NASA’s exoplanet data approachable, interactive, and fun to explore. Hosted as a public Microsoft Fabric App, it brings together more than 6,400 confirmed exoplanets, visual comparisons, and links directly to NASA’s science and catalog resources. No sign-in required. What you can explore Distances from Earth: A quarter-circle chart places Earth at the origin, with logarithmic distance bands that bring nearby and distant worlds into the same view. Markers scale with planet radius, with smaller planets toward the vertical axis and larger planets toward the horizontal axis. It’s a comparison of distance and size—not a sky map. Other systems versus our own: Compare host-star and planet radii against the Sun and Earth. Four labeled quadrants make it easy to spot combinations such as smaller stars with larger planets. Zoom each axis independently to investigate further. Details behind the dots: Search for planets and host stars, browse individual discoveries, and see measurements including orbital radius and orbital period where available. Follow a planet’s links to learn more from NASA. A focused Explore mode: Expand either chart into a screen-sized view, with compact controls on desktop and touch-friendly panels on smaller screens. Built with Fabric Apps The app uses React, TypeScript, Vite, and Microsoft Fluent UI, deployed through Fabric Apps static hosting. It’s an example of bringing an existing frontend application to Fabric without redesigning it or adding a data backend. From a static snapshot to a connected app This version bundles a NASA Exoplanet Archive snapshot with the frontend, but that’s a starting point—not a limitation. The app could be extended with a Fabric data backend, using scheduled ingestion to refresh the catalog and APIs to serve the data to the existing visualizations. That would allow new discoveries and updated measurements to appear without rebuilding and redeploying the frontend, while preserving the same exploration experience. About the data The current app uses a dated snapshot rather than a live feed. Missing measurements are identified rather than treated as zero, and NASA links provide access to the underlying science and measurement context. This is an independent project, not affiliated with or endorsed by NASA. 🚀 Explore the app 💻 View the source on GitHubCost of Living Tracker: Power BI report that breaks US inflation into categories (free to download)
Hi everyone, Headline inflation hides the real story: rent can climb while gasoline falls, and the average matches nobody’s budget. I built a Power BI report that breaks the consumer price index into the categories that make up a household budget. What’s on the page Six KPI cards for all items, food, rent, energy, medical care and transportation, each with a change since last month and a trend line A key-insight sentence and a “purchasing power of $100” card, both written with DAX and driven by a period selector (1Y to Max) A ranked bar chart of inflation by category and a price chart with three views: change vs year ago, price index and monthly change A month-by-month heatmap colored by a measure Housing, energy and food deep dives (rent vs owners’ equivalent rent, gasoline vs electricity, food at home vs away) A personal inflation view with Renter, Homeowner, Student and Retiree profiles, using illustrative spending weights How it’s built Data comes from 14 BLS price series through the FRED API, loaded in one Power Query that loops over the series list, so a bad ID only blanks that series. A category dimension table drives colors and groupings, and a disconnected table drives the period selector and the three views. The heatmap and line colors come from measures using “format by field value”. Personal inflation is a weighted sum over a profiles table. The project was built as a PBIP, so the model and report are plain text. Free to download The PBIX is free. Email [email protected] and I’ll send it. The file includes a working FRED API key, or you can replace it with your own free key inside the Cpi query. More on my site I wrote a longer walkthrough of each visual, the series codes and how to read the numbers. You’ll also find the full report there, plus my other dashboards: 👉 https://www.docynx.com/dashboard/cost-of-living-tracker-dashboard I’d like feedback on the heatmap and the personal inflation idea. Would you prefer sliders, or presets like these? Thanks for looking! Other links: Free Sample Data Generator • Create Realistic Mock Data Instantly Free XML Sitemap Generator Online – Advanced SEO Sitemap Tool Convert Image to Base64 Text Online Free For PowerBI Image embedding without Storing image on Server | PNG, JPG to Base64 Encoder Compress PDF Documents Online Explore Dashboard Gallery
