Tableaux de bord Excel et Power BI, automatisation du reporting

J'automatise le reporting des ventes : vos exports manuels deviennent des tableaux de bord et des rapports qui se mettent à jour en un clic.

Vous m'envoyez un export brut de votre ERP, CRM, logiciel de caisse ou un simple CSV. Je vous rends des données propres et vérifiées, vos KPI et un rapport prêt à envoyer, en Excel, PDF ou Power BI.

Ce que je fais :

Tableaux de bord Excel et Power BI interactifs : ventes, réalisé vs objectif, analyse ABC, clients, stocks
Rapports de ventes mensuels construits automatiquement à partir de vos exports
Rapports PDF aux couleurs de votre marque, générés en quelques secondes
Nettoyage et contrôle des données : doublons, valeurs manquantes, lignes de sous-totaux
Intégrations via API et workflows n8n

Pourquoi moi : plus de 15 ans dans le commerce de détail, dont la direction de réseaux de 10 à 30+ magasins. C'est moi qui lisais ces rapports : je sais quels chiffres un manager regarde vraiment.

Outils : Python (pandas, openpyxl, matplotlib, reportlab), Excel, Power Query, Power BI (DAX), SQL, n8n, API REST.

Exemples de projets : https://github.com/postartem-stack

— English —

I turn manual sales reporting into automated pipelines. You send a raw export from your ERP, CRM or a CSV. You get back clean, validated data, KPIs and a ready-to-send report in Excel, PDF or Power BI that refreshes with one click.

What I do: interactive Excel and Power BI dashboards (sales, plan vs actual, ABC analysis, customers, inventory), monthly sales reports built automatically from your exports, branded PDF reports, data cleaning and validation, integrations via API and n8n.

Why me: 15+ years in retail, including running store chains of 10-30+ locations. I was the one reading these reports, so I know which numbers a manager actually needs.

Portfolio

Problem: a monthly management report was built by hand from a nested ERP/1C export (merged headers, monthly blocks, subtotal rows).
Solution: a Python pipeline that runs with one command - detects the structure, flattens the hierarchy, removes subtotals, validates data quality, calculates KPIs and builds a 10-sheet Excel report with native, editable charts.
Result: hours of manual work become one run. Demo on synthetic data.
Code: https://github.com/postartem-stack/sales-reporting-automation
Problem: every month a team exports sales, recalculates KPIs, redraws charts and rebuilds the report by hand.
Solution: one Python command reads the CSV, calculates monthly KPIs and month-over-month change, builds charts in the brand palette and lays out a branded one-page PDF with KPI cards, trend, category and channel breakdowns and a top-products table.
Result: a report for any month in under 30 seconds. Demo on synthetic data of a fictional brand.
Code: https://github.com/postartem-stack/raw-thread-reporting
A slicer-driven sales dashboard in Excel on 10,000 rows: KPI cards (revenue, profit, orders, average order value), three linked charts and three slicers (region, channel, category). One click re-filters every KPI and chart. Drop in a new export and everything recalculates.
Built without pivot tables: slicers on an Excel Table, a SUBTOTAL helper column and a SUMPRODUCT calculation sheet - full freedom of design in brand colours.
Live version opens in the browser (link in the repo). Demo on synthetic data.
Files: https://github.com/postartem-stack/raw-thread-excel-dashboard