Mubasher Ali

Talent

LondonMember since June 9, 2026

Power BI DesktopInteractive dashboardsSemantic modelsDAX measuresPower QueryDrill-throughBookmarksReport navigationKPI pagesDashboard UXPower BI ServicePublishingWorkspacesAppsScheduled refreshGateway conceptsRefresh monitoringAccess/RLS conceptsDeployment pipelineT-SQLSQL viewsReporting tablesCTEsWindow functionsJoinsAggregationsReconciliationQuery optimisationAdvanced ExcelPower Pivot

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Power BI DesktopInteractive dashboardsSemantic modelsDAX measuresPower Query

About

Power BI Developer with 5+ years of experience delivering dashboards, semantic models, DAX measures, SQL reporting layers and automated MI across retail, supply chain and operational environments. Strong hands-on capability in Power BI Desktop, Power Query, DAX, T-SQL, data modelling, dashboard QA and Power BI Service deployment. Known for converting messy operational data into trusted reporting outputs, improving reporting speed by 30%, supporting 15% stock accuracy improvement and documenting KPI logic clearly for business users.

Experience

Supply Chain & Retail Analyst - Sapphire Retail Ltd

(2022-05 - 2024-01)

Built and maintained Power BI dashboards for retail performance, inventory, sales and supply chain KPIs, translating business questions into clear report pages and measures.
Automated daily sales and stock reporting using SQL, Power Query and Power BI, improving report delivery time by 30% and reducing manual Excel reporting.
Developed DAX measures and KPI logic for stock accuracy, sell-through, inventory turnover, stock cover, category performance and replenishment visibility.
Created SQL-based reporting datasets using joins, aggregations and reusable transformation logic to support refresh-ready dashboards and consistent business definitions.
Tested dashboards with merchandising, planning and operations users, resolving data quality issues, validating outputs and supporting adoption of Power BI reporting.

Data Analyst – Merchandising - Nishat Linen

(2020-02 - 2022-04)

Designed merchandising and forecasting reports using sales history, seasonal trends and stock movement data, supporting 90%+ demand forecast accuracy.
Developed operational dashboards covering inventory turnover, stock cover, sell-through rate, product availability and category performance.
Reduced inventory variance by 12% by analysing stock discrepancies, exceptions and logistics bottlenecks through SQL, Excel and dashboard monitoring.
Collaborated with planners and business users to define KPI calculations, document assumptions and improve visibility during high-demand trading periods.