Fantasy Premiere League Analytics Hub v3
Multi Seasonal Report to help Fantasy managers track player performance discover hidden gems and undervalued assets Main changes from previous version: Changed the pipeline from just python > powerbi to python >sql databae > powerbi' This was done to handle multi season analysi as the previous pipeline wasnt fit to do so Utilised bronze silver gold staging in sql More contextualised kpis Customiseable charts (parameters) Utilised HTML visuals for KPIs, Visuals (player explorrer page) and tooltips Star Schema Data Model eyJrIjoiMTVjMTdkMWEtZTQwOS00NDM0LTkxYTEtMjJmODY2ZDhmMTY0IiwidCI6ImQxMjA2OTQzLWJmY2MtNGM3NC04MmQ0LTA1ZTYzYTQzMzViZiJ9Restaurant & 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.Optimising Sidebar Navigation (expandable) for Power BI Reports: Tips and tricks
I've recently developed and tested this functionality. It requires quite a bit of bookmarking but is manageable without any performance issues. To configure this efficiently, I recommend using Visual Studio Code to edit the Power BI report (PBIP) directly in the sidebar navigation. This method allows for quicker configuration compared to manual adjustments within the PBIX file. This feature is particularly useful when working with a large number of pages in Power BI visualisations. eyJrIjoiNTNjMjVhMzctNTgwMC00MzViLWEzODMtY2RiYWNiY2ExZGM2IiwidCI6IjBmNDBhZjEwLTI5MTgtNGVlMC1iMjY1LWQ2ZjAwNjc4ZjU4NSIsImMiOjh9Daylight Check: Window to Floor Area Ratio on a BIM Model
This report checks the window to floor area ratio of a residential building level by level, directly on its BIM model. Most building codes require the glazed area to be at least one eighth of the floor area: here every level gets its ratio, compared against that threshold, and the levels that fall short turn red on the 3D model. The model is an IFC file converted into tabular data with Vcad, so glazed areas, floor areas and levels come straight from the model, with no manual schedules. How to use it: - Click a level in the bar chart or in the table to isolate it. Cards, donut, table and 3D model filter together. - Use the Level slicer to jump to a specific floor. - Switch between As designed and What-if. The what-if scenario reduces the glazing on levels 2, 8 and 14 to 35% and shows which levels stop complying. - The donut shows where the glass is, grouped by band of levels. Colors on the model: blue for glazing, yellow for levels that pass, red for levels below 1/8. The ratio is computed on the gross floor area of each level, which makes it a conservative early check rather than a room by room verification.F&B Sales Performance Dashboard
F&B Sales Intelligence Dashboard An interactive dashboard developed as part of my data analytics portfolio to explore sales performance across three F&B outlets in Indonesia. It uses the Anonymous Transactional Dataset from Mendeley Data, containing historical POS transactions and product metadata for January–September 2025. The dashboard covers sales KPIs, outlet performance, weekly trends, transaction intensity by day and operating hour, and product rankings. It also incorporates RFM-based transaction segmentation using K-Means, replicating a published methodology with the full dataset. Four transaction segments are summarized by volume, average spending, and total transaction value. The analysis covers 53,820 transactions with a total transaction value of approximately IDR 1.32 billion. Key findings include SHOP001 contributing nearly 49% of total transaction value and high-value transactions contributing a substantial share despite their smaller volume. Tools: Power BI and Google Colab (Python) Skills: Data modeling, DAX, KPI development, interactive visualization, RFM analysis, K-Means clustering, and insight communication. Dataset: https://data.mendeley.com/datasets/kcgf45y24m/2 Feedback on the dashboard’s design, analysis, and usability is welcome.DAX Reference
Overview Learning a new language can be over-whelming. Within the Data Analysis eXpression (DAX) language there are many different commands. However it is quite possible to create a professional Power BI solution using a small sub set of the commands available. Where this small sub set of DAX commands together have a much more manageable learning experience. There are two types of best practice to keep the usage of DAX as simple as possible … • Aim for your data model to be a star schema. • Perform as much transformation within the data load process as possible, either in Power Query (for Power BI) or SSIS for Analysis Services Tabular Model. If you follow the above best practices in full you will be very pleased as to how many insightful and attractive data visualisations you can easily create within a very short period of time. The examples are included within the sample AdventureWorks PowerPivot and AdventureWorks PowerBI solutions so you can gain a greater context of the example code against each function description. Please click on the following link to examine these data models. There is also a DAX query script where some example code is executed within the context of a DAX query as instead of a column or measure within a model. Please download DAX Studio https://daxstudio.org/ to view / analyse and run the DAX query scripts. Training Details of training on Power BI is available from https://www.dataplatformservices.com/ eyJrIjoiYzQ0ZjJmYzItNTNlZi00YmFlLWFlMDAtOTA3MjYwMjlkYzYzIiwidCI6ImY1NmM4YzIyLTQ5ZDMtNDQ5OC1iZThiLWU3MWE0YjVlZGRjNiIsImMiOjh9&pageName=ReportSectionPower BI Best Practice Recommendation
Power BI Best Practice Recommendation This Adventure Works Power BI solution shows example best practice recommendation. Please click on the (i)information buttons on each page for further reading. Training Details of training on Power BI is available from https://www.dataplatformservices.com/ About the Author Kieran Wood is a UK based consultant and trainer focusing on Power BI and SQL Server Analysis Services related technologies such as DAX and MDX. Website: https://www.dataplatformservices.com/ Twitter: https://twitter.com/KieranIBI LinkedIn: http://www.linkedin.com/in/kieranpatrickwood Blog: http://kieranwood.wordpress.com/ eyJrIjoiYmJkNWU3MmQtMGQwNi00M2VjLThlYTAtMWQyZDdhYzI1ZjUxIiwidCI6ImY1NmM4YzIyLTQ5ZDMtNDQ5OC1iZThiLWU3MWE0YjVlZGRjNiIsImMiOjh9The 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 #MicrosoftPowerBISales and Financial Performance
Sales and Finance Dashboard Why a unified Sales & Finance dashboard matters (and what it actually fixes) The Importance of This Dashboard Most teams split sales tracking from financial reporting. Sales sees revenue; Finance sees cost. They rarely meet in one place until it’s too late. This dashboard exists to close that gap. It connects execution to profitability. You can move from an executive summary down to the individual transaction without switching tools. It shifts the conversation from “How much did we sell?” to “What did we actually earn?” Profit, COGS, margin, and cost-per-unit are built in—not calculated separately. It serves both micro and macro decisions. The same structure supports a rep reviewing their profile, a manager coaching a team, or a leadership team reviewing monthly trends. It replaces scattered reports with one interactive source. Year, country, category, and product filters apply across views, so the data stays consistent. Key Benefits of Having It For Sales Managers & Team Leads Manage by profit contribution, not just revenue. Identify which countries, categories, or users are pulling the team down. Compare team/rep performance on a common baseline. For Finance / Controllers / CFO Monitor true profitability by geography and product line. See cost structure (COGS) directly against revenue without manual reconciliation. Validate margin efficiency at a glance. For Executives / Leadership Get a high-level pulse (revenue, profit, shipments, trends) instantly. Spot concentration risk and monthly shifts without waiting for static reports. Make faster strategic calls backed by consistent data. For Operations / Analysts Drill from summary to line-item detail when needed. Filter, search, and audit individual transactions by date, rep, country, or product. Reduce time spent stitching spreadsheets together. For Individual Sales Reps Understand their full impact—revenue, units, profit, and margin—not just a top-line number. Track YoY progress in one view rather than across multiple files. Bottom Line Benefit You stop making decisions on half the story. Revenue without cost is misleading; cost without sales context is blind. This brings both into one workflow, faster decisions, clearer accountability, and less reporting overhead. For more, visit: https://arbazahmad-bi.netlify.app/ Thank you.Dubai Real Estate Insights | Where data meets decisive property strategy.
About the Report: The Dubai Real Estate Insights Dashboard is an interactive analytics platform designed to deliver a holistic view of Dubai’s real estate performance. It serves as a centralized, visual cockpit for executives, analysts, and stakeholders to monitor market trends, property transactions, and sector dynamics in real time. Built for clarity and decision impact, the dashboard translates raw data into actionable insights, enabling better understanding of market health, sales activity, and channel performance across locations, time periods, and property categories. Need for the Report: The Dubai property market is fast-moving, data-intensive, and highly segmented. Decision-makers require timely, consolidated, and visual insights to identify emerging opportunities and manage portfolio risks effectively. This report meets the need for a unified, automated view that empowers leadership to make evidence-based strategic and investment decisions. Usage: Executives: For high-level performance tracking and strategic market evaluation. Analysts and Advisors: To explore sub-market trends, buyer behavior, and sales channels. Developers and Investors: For demand forecasting, price benchmarking, and identifying high-growth segments. Key Insights: Combines summary metrics and drill-down analytics for a 360° market view. Enables trend tracking across property types, locations, and sales channels. Facilitates comparative analysis to measure performance against benchmarks. Technology Used: Developed using Microsoft Power BI, leveraging: Dynamic dashboards for real-time updates and intuitive exploration. DAX-based measures for accurate KPI calculation and comparative insights. Data modeling for integrating sales, transaction, and market datasets. Row-level security and role-based access for controlled visibility. Automated refresh and drill-through features for enhanced interactivity. Skills: Microsoft Power BI · Microsoft Copilot · Data Modeling · Data Scraping · Extract, Transform, Load (ETL) · Data Governance · Python (Programming Language) · Data Cleaning · DAX eyJrIjoiNzA1ZmUyM2YtODc3Mi00NTgxLTk1YzYtNmExNjY1NzFhZmY3IiwidCI6IjkyNTcwMDE0LWZmM2QtNDAxMC04MTNkLTQxM2YwZmY5OWQ5MiJ9
