Restaurant & Menu Engineering — Analysis
Most dashboards answer questions. Very few tell you what to do on Monday. I rebuilt a restaurant analytics report this week and spent as much time on the narrative as the numbers. What that meant in practice: Every page ends with a written read-out panel. Not a KPI. An actual sentence explaining what the chart means and what it implies. "Labour averages 23.2% of sales, but The Bistro Table runs 60.4%, and it is a scheduling problem, not a menu problem." Colour carries meaning, not decoration. Stars are teal, Plow Horses blue, Puzzles amber, Dogs coral, and those four colours mean the same thing on every page. The menu engineering matrix uses reference lines at the actual portfolio benchmarks, so the quadrants are real thresholds rather than eyeballed corners. The icon set is hand-drawn SVG rather than stock clipart, rendered at 4x so it stays crisp on any display. Shipped in both a dark and a light theme. And a final page that does nothing but list the three model issues I found and the corrected DAX to fix them. If the numbers are wrong, the design is decoration. Six pages. One dataset. 17 venues, 167 menu items. Happy to share the DAX fix pack if it is useful to anyone.Grão Raro: assinaturas de café especial
Relatório de acompanhamento de um clube de assinatura de cafés especiais. A Grão Raro é uma empresa fictícia e todos os dados são fictícios, criados para este portfólio. O relatório foi pensado para quem gerencia a operação de assinaturas: receita, base de assinantes, cancelamentos e entregas, um mês de cada vez, com comparação contra o mês anterior. Visão geral: o resumo do mês. Receita recorrente, assinantes ativos, novas assinaturas e taxa de cancelamento, com a receita por mês e plano, o saldo semanal de entradas e saídas, os cafés mais pedidos, o mapa de assinantes por estado e a preferência de torra. Manual do relatório: o que cada página mostra e como usar cada controle. As páginas Assinantes, Cancelamentos e Pedidos e entregas estão em construção e aparecem no menu com cadeado. Recursos de experiência de uso: Central de ajuda: uma janela de conversa, aberta pelo menu, que simula uma assistente de IA dentro do relatório. A pessoa digita uma pergunta em linguagem natural (“quanto faturou em março?”, “qual café mais vende no Sul?”, “quantos cancelaram por região?”) ou escolhe uma sugestão por assunto, e recebe o número, a comparação, um mini gráfico de barras e, quando cabe, a foto do café. Responde para qualquer mês, por café, torra, região, plano e canal. A conversa é mantida ao trocar de página, e há botões de nova conversa, copiar e avaliar a resposta. Filtros: reunidos em um painel próprio, em botões com estado de hover, com contador de filtros ativos e Limpar filtros. Manual e tour guiado: a página Manual do relatório descreve cada página e cada controle, e o tour “Como usar” apresenta os recursos passo a passo. Acessibilidade: contraste no nível AA em todos os textos, e todos os indicadores batem com os visuais de onde saem.
Student Performance Dashboard Project
Student Performance Dashboard This project is an interactive Student Performance Dashboard developed using Microsoft Power BI to analyze and visualize academic performance through dynamic reports and KPIs. Dashboard Features Overall Student Performance Overview Subject-wise Performance Analysis Gender-wise Performance Analysis Interactive KPI Cards Grade Distribution Analysis Top 5 Performing Students Average Percentage & Highest Percentage Section-wise Performance Comparison Dynamic Charts and Summary Tables Tools & Technologies Microsoft Power BI Power Query DAX (Data Analysis Expressions) Data Modeling Key Insights The dashboard enables users to: Monitor overall student performance. Compare subject-wise academic results. Analyze gender-based performance. Identify top-performing students and grade trends. Make data-driven educational decisions through interactive visualizations. I would appreciate your feedback and suggestions to improve this dashboard. Thank you for taking the time to review my project. Developed by: Syed Raahim Ali Course: Data Analytics & BI eyJrIjoiMGM0OWY1MGUtMTk5Yy00MDNmLTllMDItN2EwNWVlNDU3NGU5IiwidCI6IjI0MWNlN2VlLTVjYmUtNDczNi1hYWM0LWZkOWZmM2NjMWRkMSIsImMiOjl9Emergency Department Operations: patient flow, triage and a shift staffing simulator
Description This report follows a fictitious network of six emergency departments through one month of care: August 2026, 47,357 visits. It was designed for the medical coordination team, and the question behind every page is where and when the team needs reinforcement. All data is made up, with no real patients or hospitals involved. The report is in Brazilian Portuguese. The eight pages follow the patient's path: Overview, Patient flow, Triage, Journey to the doctor, Left without being seen, Outcome, Returns within 72 hours, and a Detail page for drill-through. What to look for: Overview: the five KPI cards are also selectors. Clicking one switches the charts on the page to that metric. The Manchester triage colors stay off until you turn on the Colors toggle, so the page doesn't open as a rainbow. Patient flow: average arrivals by hour and weekday, plus a staffing simulator. Sliders set the doctors on duty in each shift (overnight, morning, afternoon and evening) and how many patients a doctor sees per hour. The matrix shows the occupancy of the busiest unit in every hour of a typical week in three bands: idle team below 60%, adequate from 60% to 85%, overloaded above 85%. It runs on what-if parameters, a matrix colored by measure and bookmarks. Triage: nurses needed against nurses scheduled, hour by hour, and how many hours each unit runs short. Journey: a timeline of the stages from arrival to the doctor, with door-to-doctor time by unit and by arrival hour. Left without being seen: the stage where patients give up, and a quadrant chart of that rate against door-to-doctor time, with the alert zone shaded. Returns within 72 hours: a Pareto chart of diagnosis groups. Detail: right-click a unit, specialty or risk bar anywhere to drill through. The title names the slice you came from, and the table uses data bars and native status icons against the 85% target, with the rule in the tooltip. A guided tour opens from the "Como usar" button and walks through each page with bookmarks. The report was first designed as an HTML mockup to settle layout and hierarchy, then built in Power BI on a star schema. Text contrast meets WCAG AA, and color never carries meaning on its own: every color comes with a label or an icon.Single-Page Power BI Report. Gender Pay imbalances in the UK. 2017-2025 — Analytical Overview
📊UK Gender Pay Gap — Analytical Overview (Single-Page Power BI Report) This is a single-page interactive report to explore gender pay differences in the UK, focusing on pay gaps, bonus eligibility, and gender representation across pay quartiles. 🔍What this report shows: 📉Mean vs median pay gap over time — highlighting structural vs distributional inequality 💰Bonus eligibility by gender and how the gap evolves year-over-year 🧱 Pay quartiles analysis — clear evidence of vertical segregation (“glass ceiling”) 📊Sector comparison — highest and lowest female representation in top pay quartile ⚖️Pay gap severity distribution — most companies remain far from parity 📈Key insight: Even when overall gaps narrow, women remain underrepresented in the top pay quartile, and progress is uneven across sectors. Equality at the bottom does not automatically translate into equality at the top. 🧠 Why a single-page design? All insights live on one canvas — enabling fast comparison, narrative flow, and decision-ready analysis without page switching. 🛠️ Built with: Power BI · DAX · Analytical storytelling 📂Data source: UK Government Gender Pay Gap Service eyJrIjoiN2ZjNmFhMjctMzg0ZS00MjJiLWJmNjUtMjcwZWY1MTZjMWVkIiwidCI6IjY1NWVhZjVhLTBhMTctNDEzOS05NzU5LTFlMDIzMTRkMDJhYiIsImMiOjZ9Bringing Microsoft DAX documentation to life in Power BI (DAX Navigator)
As Power BI developers, analysts, and data professionals, we've all experienced the same challenge. You know there is a DAX function that can solve your problem, but you can't remember its exact name, syntax, or category. The usual process is to leave Power BI, open a web browser, search Microsoft's documentation, navigate through multiple pages, and then return to your report. While Microsoft's DAX documentation is an incredible resource, constantly switching between Power BI and the browser breaks the flow of learning and development. I wanted to create a different experience. That's why I built DAX Navigator, an interactive Power BI report designed to help users discover, explore, learn, and understand DAX functions without leaving the Power BI environment. The journey begins with a function category selection page. Users can browse categories such as Date & Time, Logical, Math & Trigonometry, Statistical, Text, Information, and Filter functions. Instead of searching for a function name, they can start by exploring the type of calculation they want to achieve. Once a category is selected, users are taken to the function browser page. Here, functions are displayed in an intuitive and interactive format. Simply hovering over a function reveals a short description, allowing users to quickly understand its purpose before opening its details. For more experienced users who already know what they are looking for, the report provides a direct navigation mechanism. Users can browse functions alphabetically and instantly jump to the desired section. The alphabetical selector dynamically highlights available letters while graying out letters that have no associated functions. The selected letter is emphasized, making navigation fast and intuitive. After selecting a function, users are taken to a detailed information page where they can view: ✅ Function description ✅ Syntax ✅ Practical example ✅ Key usage information ✅ Related category ✅ Direct link to official Microsoft documentation When additional details are needed, users can seamlessly open the corresponding Microsoft documentation page with a single click. What makes this solution even more powerful is that the content is not manually maintained. The function catalog, descriptions, examples, and documentation references are sourced directly from Microsoft's official DAX documentation, ensuring that the information remains aligned with the latest updates published by Microsoft. Instead of relying on static references, the report acts as a live and interactive gateway to Microsoft's DAX ecosystem. The goal was to create a bridge between discovery and documentation. A place where users can explore DAX naturally, learn through examples, understand functions faster, and access official references when they need deeper technical details. Whether you're a beginner taking your first steps into DAX or an experienced developer looking for a quick reference tool, DAX Navigator transforms documentation into an engaging, interactive learning experience directly inside Power BI. DAX Navigator combines the reliability of Microsoft's official DAX documentation with the interactivity of Power BI, creating a single place to discover, learn, and master DAX functions. Because sometimes the fastest way to learn DAX isn't searching for a function... It's discovering it.
Live Weather Dashboard
Live IoT Weather Dashboard This is a real-time weather dashboard powered by a custom-built DIY IoT weather station. While many weather dashboards available online use static datasets or merely change color schemes on the same template, this project is fundamentally different. It is a live system that bridges the gap between physical hardware and digital analytics. Technical Overview Data Collection: Unlike dashboards that rely on CSV uploads, this station utilizes an ESP8266 microcontroller paired with DHT11 and BMP280 sensors. Live readings for Temperature, Humidity, and Pressure are logged directly to Google Sheets in real-time. Region-Specific Calibration: Specifically calibrated for the unique tropical climate of the Trichy, Tamil Nadu region, ensuring localized accuracy that global APIs often miss. Advanced Analytics: Using only four raw data points (Timestamp, Temp, Humidity, and Pressure), I have developed a custom suite of DAX measures. These calculate complex weather trends, "feels like" temperatures (Heat Index), and atmospheric dew points. Dynamic Visuals: The interface isn't just a static skin; it features weather-dependent iconography and a custom refresh schema that ensures the data you see is as fresh as the air outside. Why this stands out Most dashboards you see are "re-skins" of existing templates. This project demonstrates a full-stack data engineering pipeline: Sensor → Microcontroller → Cloud Storage → Power BI Logic → End-User Visualization. eyJrIjoiYTVjNzg4MzMtZDJlMS00NmY5LWI1ZDItNzRhMjRmNDdkZWIwIiwidCI6IjBjM2QwNTc2LTFkOWYtNGM4Ny05OTNjLTg2YjQ0MGE1YjA3OCJ9Project Management Dashboard
This project management dashboard is essential because it provides a centralized, visual overview of project progress, making it easier to track tasks, deadlines, resources, and budgets, as well as identify potential issues early. This centralized view improves communication, streamlines decision-making, and ultimately helps keep projects on track and within budget. Why project management dashboards are so important: Real-time visibility: Dashboards offer a quick and clear view of a project's status, allowing teams and stakeholders to instantly see progress and identify potential issues. Improved communication: By providing a single source of truth for the project, dashboards reduce the need for constant updates and follow-ups, fostering better communication between team members and stakeholders. Improved decision-making: With clear and concise data readily available, project managers and stakeholders can make informed decisions based on real-time information. Efficient Resource Allocation: Dashboards help track resource utilization, ensuring they are allocated effectively and that no team member is overburdened. Early Risk Identification: By monitoring key metrics and trends, dashboards can help identify risks and potential issues before they escalate, enabling timely intervention. Increased Accountability: With clear visibility into who is responsible for each task, dashboards can help promote accountability and ensure deadlines are met. Improved Project Execution: Ultimately, the benefits of a project management dashboard contribute to better results, including on-time delivery, on-budget completion, and improved team performance. Visit Website: https://insight-analytics.com/dashboards/ Thank you eyJrIjoiY2MyZTRlZjgtMWM1MC00NWY0LWFlNmQtZWZiNDQ4OGZjNGQ0IiwidCI6IjBlMGNiMDYwLTA5YWQtNDlmNS1hMDA1LTY4YjliNDlhYTFmNiIsImMiOjR9The Finance Dashboard
The Finance Dashboard | Power BI Project 📊 Excited to share my latest Finance Dashboard built using Microsoft Power BI! This project focuses on Financial Data Analytics, Business Intelligence, and Interactive Data Visualization. Key Features: - Total Amount, Tax, Fees & Final Amount KPIs - Country-wise Financial Analysis - Company-wise Amount Analysis - Transaction Status Monitoring - Tax Analysis by Country & Company - Year & Account Type Filters - Interactive Dashboard Design This dashboard helps transform raw financial data into meaningful insights for better business reporting and data-driven decision-making. Tools: Microsoft Power BI | Data Analytics | Business Intelligence | Financial Reporting I am passionate about Data Analytics, Power BI, and turning data into actionable business insights. Your feedback is welcome! #PowerBI #PowerBIDashboard #DataAnalytics #BusinessIntelligence #FinancialAnalytics #DataVisualization #FinanceDashboard #PowerBIDeveloper #DataAnalyst #MicrosoftPowerBITrucking Operations Analytics - From Data to Decisions
I’m excited to share this interactive portfolio project, a landing page that centralizes all operational analytics in one place. It's designed for both executives and operations leaders. A 16-minute walkthrough of the solution is available on YouTube. This report delivers an app-like experience with intuitive navigation, KPI scorecards, ranking logic, and scenario modeling across key operational domains including driver performance and tiering. The focus was not just reporting, but decision enablement by ranking drivers fairly, identifying unprofitable lanes, quantifying the cost of downtime, and supporting “what-if” operational scenarios. Three year customer revenue history with YoY variance and CAGR calculation to support strategic financial planning and account prioritization. It also quantifies detention impacts using a 2-hour free wait policy and dynamic rate parameters. Which enables real-world analysis for evaluating contract terms, detention policies, and earnings impact. It's built with an end-to-end analytics first modeling, and C-suite executive ready visuals. Along with a complete documentation page defining all KPI formulas, owners, and data sources to ensure trust, transparency, and governance. This solution demonstrates how Microsoft Fabric, a modern data platform can drive operational efficiency, cost optimization, and performance accountability at scale. I’d value the community’s perspective on the following: Among the pages in this solution, which one delivers the strongest operational value, and what enhancement would you prioritize next? In your experience, should operational dashboards focus more on KPI tracking, or on explaining why performance is changing? If you were in the logistics industry, what’s the biggest hidden opportunities cost in trucking operations that analytics helped you uncover? Detention, Downtime, Fuel, or Something else? Your insights will directly inform the next iteration of this solution. eyJrIjoiNzI1MDJhNTMtMTk4NS00YzI4LTg4NTItYzcxNDZiYjc0ZWQzIiwidCI6IjNlMjFhMTFlLTc3MDctNDdmOC1iMzRhLTc5YTQ2YTQ0ZTk5MyIsImMiOjF9
