Decoding the Unknown - Survey & Fear Analytics (Halloween Contest Entry)
About the Poster: I made this single-page dashboard as an A4 standalone poster. My main goal was to tell a simple story about what scares the data community in childhood versus what scares them today as adults. Key Insights from the Data: - Biggest Current Fear: 'Animals & Insects' is the most common active fear for adults (76 entries). - Hardest Fear to Forget: 'Confined & Physical Spaces' is the most stubborn fear. 33% of people who feared this in childhood still fear it today. - Top Location: Europe is the biggest hotspot, with the most responses in the survey (356 entries). Design Choice: I used a dark theme with neon highlights and an easy-to-read Matrix chart. The design is simple so anyone can understand the full story easily at a glance, without needing to click or hover on anything.
The Fear Files | What Changes, What Lingers?
What keeps us up at night changes over time. The Fear Files compares childhood fears with present-day fears using 105 responses from the Power BI community. Some fears fade: 48 respondents selected a fear in the Unknown & Supernatural category for childhood, compared with 14 for today. Others grow: mentions of war rise from 5 to 19, and uncertainty about the future from 4 to 14. Meanwhile, 45 respondents selected at least one identical fear in both life stages. This single-page A4 landscape report combins data storytelling with Halloween-inspired visuals and animation. All analytical findings come from the supplied survey. The sample is self-selected, so these results describe the respondents, not the wider population. The PBIX file is attached.Workout Wednesday 2026 Week 41: Stripe Chart Using Native Column Chart
This week's challenge is from Santhana Lakshmi Ponnurasan. What if a column chart could tell a story through color? A stripe chart uses colored stripes to reveal patterns and changes in data at a glance. In this exercise, we’ll transform Power BI’s native column chart into a stripe chart where each stripe represents a data point, and its color helps us spot patterns, changes, and unusual values. Same visual, a different way to see the data. Ready to give your column chart a makeover? For more info, see: https://www.workout-wednesday.com/pbi-2026-w41/World Champs BCN 26 - Finale - SQL Radar · Find the signal before the alarm
Hello the Community, Here is my Barcelona Finale report. Nothing's broken. Officially. That was my starting point: no SQL system had crossed a critical threshold, yet several were clearly drifting. So I built this report around three simple questions, one page each: 1. Signal: where are the problems? A pill table shows, for every system, its threshold, headroom and drift status. Three charts and a map show what is moving, and where. 2. Diagnosis: why is it moving? For the selected system, a timeline shows when each metric left its August normal, and a table checks every metric against the last assessment: is it new, is it explained, is it shared with another system? 3. Action: what do we do first? A criticality-versus-signal matrix and a runway timeline rank the systems, and the plan gives each one an action and a deadline. One click sends the brief by email. On the design side, I deliberately split the work in two. Native visuals carry the data and the interactions (the table that filters the page, the charts, the matrix and their report-page tooltips). HTML carries the experience: the map that zooms on the selected site, the animated timelines, the identity cards and the intro. And there is a little assistant on every page. In light mode, Mercury, a drop of liquid metal, sums up the page in one sentence and answers a few questions. Switch the light off, and Glitch, a pixel bug who lives in your SQL logs, takes over with the same insights and a lot more attitude. Find the signal, understand it, act on it. Hope you enjoy the ride! You liked my report ? You can find me here on linkedin for more content : Aanor Le Gouic | LinkedInWorld Champs BCN 26 - Finale - AstraVale - Operational Health
This report was built from the perspective of an AstraVale employee responsible for keeping the company’s systems running reliably. It is designed to answer three questions: Which systems need attention? What happened? And are there other related systems that could also be affected? Operational Overview - Which systems need attention? This page gives an overall picture of system health and helps the user decide where to start. You can get an immediate picture of system health from the KPI cards at the top. They show how many systems need investigation, how many need review or watching, and how many are within limits. You can click each card to focus on that group of systems. The "Where to focus" table shows which systems need investigation, which need review, and which should be watched. The trend beside each system shows the pattern of recent breaches, while the signal squares explain which rules have been met and contributed to its priority. Users can hover over the information icon to learn what those rules mean. The interactive globe adds a view of the facilities and lets the user narrow the page to one location. The assessment summary shows where checks have failed and how serious those findings are. System Investigation - What happened? After identifying a system that needs attention, the user can explore it in more detail on this page. The system information "i" icon provides context about its purpose and importance, while the monitoring visuals help explain its behaviour. The heatmap makes it easier to spot unusual days and see which metrics were involved. The "Top priority" mark highlights the metric to look at first, giving you a clear starting point for your investigation. You can then select a metric and use the hourly chart to see when it changed, how long the issue lasted, and whether it returned to its expected range. This helps distinguish a short spike from a more sustained issue. The assessment history provides another part of the picture. It shows how check results have changed between assessments, helping the user see whether findings are new, recurring, or have been resolved. Connected Operations - Could related systems also be affected? This page helps the user look beyond a single system. Systems can be grouped by a shared dependency, physical facility, hosting region, or another connection. These relationships show where it may be useful to investigate next. The percentages beside each system show how its average changed between the selected baseline and comparison periods. This gives a quick way to see which systems changed the most. The line chart shows how that change developed day by day. In the relative view, every point compares that day’s average with its baseline. This makes it easier to see whether related systems changed at a similar time or followed different patterns. ---------------- The finals were an incredible experience, and I'm so grateful for everything I learned, the people I met, and the chance to be part of it all!😄 If you’re thinking about participating, go for it – I promise it’s an experience you won’t forget!😀World Champs BCN 26 - Finale - The Weight of Waiting by Jerome Ian Arbonida
THE WEIGHT OF WAITING Landing What if I told you that the most technical dataset I have ever received… could teach us something very human? This is The Weight of Waiting. Someone is waiting while systems are working. We can measure the delay. But what does that delay take away? Welcome to Astravale. Page 1 This is the world of Astravale. Equal — but not in weight. Each site carries a different weight, represented through four signals: Workload, Pressure, Room, and Waiting. And when we sliced the data to the latest date, something stood out. Only one site remained in red. And since waiting has weight… we should meet the Weightbearer. Page 2 This is the Atacama Deep Space Station, carrying the weight of Astravale through its Mission Critical Helios Telemetry system. The data starts to tell us a story. As activity rises, pressure rises with it. Memory and storage remain relatively stable, following their own trends. But one signal caught my attention. Waiting. As activity increases, blocked sessions and deadlocks increase too. So the question becomes: Is the system failing? Let’s go deeper. Page 3 Still in Atacama, we can again see activity rising significantly. But technical findings? They stay flat. And that tells us something important. The system isn’t failing. It’s working. It’s just… overworked. And who carries the consequence of that? Us. The humans behind the systems. Page 4 And now… I want to reveal the true weight of waiting. Because in this world of data, technology, and AI… let this dashboard remind us: our currency isn’t tokens. It’s time. [25-second interaction / show what happened to Astro that day] Maybe you can relate to Astro. As a parent. A brother. A sister. Or maybe… some of us were once the Astro who waited. So my hope is simple: Let’s unload the weights. I hope we don’t miss a home-cooked meal while we make our systems more efficient. I hope we don’t miss a bedtime story while we turn pressure into performance. I hope we always get to say goodnight. And when home finally gets quiet… I hope we still have a little energy left to give. Because behind every workload, every alert, every data point… there is a human being waiting for someone. And as we leave this conference and go home to the people we love… I hope we remember to thank them. The ones who patiently, quietly, and lovingly… carried the weight of waiting with us. Gracias, Barcelona. Maraming salamat, at mabuhay tayong lahat. Thank you.World Champion Winner - Live Finale Build - AstraVale SQL health report by Marius Helle
🏆 2026 Power BI Dataviz World Championship Fabcon Barcelona finale winner. AstraVale SQL health report The report takes the reader from a broad overview to a clear plan. It starts with all systems, then narrows down to what has changed, why it happens, how the problems are connected, and what to do first. Each page builds on the one before. Overview: shows all systems on a map and in a table, coloured by status, with equipment value and alarms. The buttons filter the view to all systems, those getting worse, or those that are steady. Problems: compares each system with its own August level to separate new problems from old ones. The buttons switch between where to start (equipment value against rising metrics), recent changes (a heatmap of every metric), and where the alarms come from (alarm hours per metric). Causes: looks at why the problems happen. The buttons switch between memory use over an average day, comparing servers the company runs itself with Azure SQL, and a chain that follows how strain builds up from CPU to blocked sessions and deadlocks. Connections: follows disk load day by day for the systems that are getting worse, compared with their own August level. The buttons test two possible links between them: systems at the same site, and systems that read from the same data feed. Action: turns the findings into a plan. The buttons switch between what happens if nothing is done, using a slider to move forward in time, and a ranked list of fixes where a slider shifts the priority from what is most urgent to what protects the most equipment. The dataset contains hourly monitoring from 10 SQL databases on Azure at 7 sites, from 1 August to 16 September 2026. Each database is measured on 8 metrics, such as CPU, memory, disk load and blocked sessions, and each metric has a warning limit and a critical limit. The dataset also includes the value of the equipment that depends on each system, which sites and data feeds the systems share, and results from regular health checks. The finals was an unforgettable experience and i'm grateful for all that the inspiration this forum has brought me😄 Please feel free to connect on linkedin: www.linkedin.com/in/mariusjhelleKanban Board
A sales pipeline where moving a card changes more than its column. Drag individual deals or a group of cards between stages and watch the weighted forecast update. Capacity limits, keyboard moves, and undo make the board as practical as it is tactile. The board is live connected to a database so moving cards between columns updates and saves automatically.Retail Store Product Placement & Performance
When I worked in retail analytics, one question kept coming up: how does where we place a product relate to how well it sells? We could analyze sales and foot traffic, but connecting those numbers to the physical store- the laptop tables, individual display positions, and endcaps- was harder. Product launches and remodels made that picture even more complicated. Placement Lab is a Fabric App that brings that context into a dashboard. An interactive isometric floor plan puts the store at the center: select a table or an individual laptop to explore its performance, switch between sales and traffic views, and compare dated layouts to see what moved and how results changed. Surrounding analytics keep the detail connected to the bigger picture. You can also experiment with fixture positions without confusing a proposed layout with measured results. Built with illustrative sample data and representative generated product imagery, it explores a long-standing ambition: understanding not just what sold, but where it sat, what happened around it, and what changed over time.
