SQL-Python Power BI Dashboard
Budget: $2 – $8 USD
Polished Project Brief — Power BI Business-Performance Dashboard
Project overview
I need an interactive business-performance dashboard built in Power BI that consolidates data from our SQL database and multiple Excel/CSV exports. The core focus is tracking Sales & Revenue and Customer Acquisition & Retention — all data modelling and visual choices should prioritise these two KPI pillars.
Scope & workflow
• SQL: Extract required tables from the source database. Provide well-documented queries including any aggregations or window functions needed to produce analysis-ready joins.
• ETL (Python): Where the SQL schema does not align with spreadsheet drops, use Python (Pandas preferred) for lightweight ETL: column standardisation, data-type fixes, and derived fields (e.g., churn, LTV, cohort dates). Final transformed outputs should load to Power BI without manual intervention.
• Power BI: Build a star schema data model with correct relationships and create DAX measures for revenue growth, new vs. returning customers, CAC, CLV, and supporting ratios. Implement dynamic date slicers, drill-through, and conditional formatting to highlight underperforming segments.
• Performance: Optimise SQL and DAX for efficiency so the dashboard refreshes on demand and scales with data volume growth.
Deliverables
PBIX file with data model, visuals, and all DAX measures.
Reusable SQL scripts and Python notebooks (clean, commented).
README (max 2 pages) explaining refresh steps, gateway settings, and deployment notes.
(Optional but desired) Short walkthrough video (5–10 min) or screenshot samples of key pages.
Technical details & expectations
• The report should support drill-down from company level to product/region and include executive summary KPIs.
• Dashboard refresh should be achievable via Power BI Desktop refresh/Gateway (document setup).
• Please highlight any prior experience with revenue or retention analytics and include sample screenshots if available.
Logistics
• Preferred timeline: [insert timeframe, e.g., 3 weeks]
• Data volume: [insert estimate, e.g., ~500k rows monthly]
• Access: I will provide read-only DB credentials and example Excel/CSV exports.
• Acceptance criteria: PBIX + scripts + README delivered, and brief handover call or recording.
Project overview
I need an interactive business-performance dashboard built in Power BI that consolidates data from our SQL database and multiple Excel/CSV exports. The core focus is tracking Sales & Revenue and Customer Acquisition & Retention — all data modelling and visual choices should prioritise these two KPI pillars.
Scope & workflow
• SQL: Extract required tables from the source database. Provide well-documented queries including any aggregations or window functions needed to produce analysis-ready joins.
• ETL (Python): Where the SQL schema does not align with spreadsheet drops, use Python (Pandas preferred) for lightweight ETL: column standardisation, data-type fixes, and derived fields (e.g., churn, LTV, cohort dates). Final transformed outputs should load to Power BI without manual intervention.
• Power BI: Build a star schema data model with correct relationships and create DAX measures for revenue growth, new vs. returning customers, CAC, CLV, and supporting ratios. Implement dynamic date slicers, drill-through, and conditional formatting to highlight underperforming segments.
• Performance: Optimise SQL and DAX for efficiency so the dashboard refreshes on demand and scales with data volume growth.
Deliverables
PBIX file with data model, visuals, and all DAX measures.
Reusable SQL scripts and Python notebooks (clean, commented).
README (max 2 pages) explaining refresh steps, gateway settings, and deployment notes.
(Optional but desired) Short walkthrough video (5–10 min) or screenshot samples of key pages.
Technical details & expectations
• The report should support drill-down from company level to product/region and include executive summary KPIs.
• Dashboard refresh should be achievable via Power BI Desktop refresh/Gateway (document setup).
• Please highlight any prior experience with revenue or retention analytics and include sample screenshots if available.
Logistics
• Preferred timeline: [insert timeframe, e.g., 3 weeks]
• Data volume: [insert estimate, e.g., ~500k rows monthly]
• Access: I will provide read-only DB credentials and example Excel/CSV exports.
• Acceptance criteria: PBIX + scripts + README delivered, and brief handover call or recording.
Related categories:
Python
SQL
MySQL
Database Programming
Data Visualization
Data Analysis
Power BI
ETL
Data Modeling
Pandas