Data cleaning and BI so Odoo numbers mean something.

Business intelligence on dirty data is theatre. Techit pairs data cleaning with BI, so KPIs, donor packs, and outlet scorecards sit on records you can defend in an audit.

Data cleaning

• Deduplicate partners & products

  Merge duplicates without breaking open orders, invoices, or stock history.

• Chart of accounts & journals

  Rationalize CoA, fix misposts, and set opening balances finance can stand behind.

• Import hygiene

  Validated Excel/CSV loads for products, partners, stock, budgets, dry-run first, production second.

• Legacy migration cleanup

  Map fields from spreadsheets or another ERP, stage loads, and reconcile before cutover.

Business intelligence & analytics

• Executive & ops dashboards

  Sales by outlet, stock health, cash position, budget vs actual, pipeline, live in Odoo, not a weekly spreadsheet rebuild.

• KPI & management reports

  PDF/Excel packs for board, donors, or branch managers, custom layouts, filters, and scheduled delivery where useful.

• Retail & POS analytics

  Session performance, commission summaries, slow movers, and cross-shop comparisons.

• NGO & donor analytics

  Burn rates, co-financing shares, voucher pipelines, and funder-ready views by project and budget line.

Frequently asked questions

• Should we build BI dashboards before cleaning Odoo data?

  No, data cleaning before dashboards is the sequence we recommend. Fix masters and opening balances first, then KPIs leadership can defend.
• Can you clean data without re-implementing Odoo?

  Yes. Targeted deduplication, CoA fixes, and import validation on staging or live, scoped to the mess you have.
• Do you support NGO and retail analytics?

  Yes. Donor burn rates and budget vs actual; outlet POS performance and commission packs, after dimensions are consistent.