One warehouse for all your data, not one spreadsheet per department.
Your operational data is scattered across ERP, WMS, CRM, MES, spreadsheets, and shared drives. Every report requires someone to pull data from 3\u20134 systems and reconcile it manually. We centralize everything into a cloud data warehouse with automated pipelines so your analytics run on a single, consistent source of truth.
Data Trapped in Silos That Don\u2019t Talk to Each Other
Service Scope
Deploy Snowflake, BigQuery, or Azure Synapse as your central analytics warehouse. Schema designed for manufacturing data models \u2014 orders, inventory, production, quality, and financials.
Automated extraction from Odoo and legacy ERP systems via Python pipelines. Transaction data, master data, and configuration data pulled on schedule or in near-real-time.
Warehouse transactions, production completions, quality records, and shop-floor data integrated alongside ERP data. The warehouse sees the full operational picture.
Scheduled and event-driven data pipelines that extract, transform, and load data from source systems. Built-in data quality checks, deduplication, and standardization at every stage.
Validation rules, anomaly detection, and data quality scoring applied during ingestion. Bad data is flagged and quarantined \u2014 not loaded into the warehouse to corrupt downstream reports.
Business-friendly data models that define "revenue," "inventory," "on-time delivery," and other metrics once. Every dashboard and report uses the same definitions \u2014 no more conflicting numbers.
Engagement Process
Catalog every data source, document data volumes, update frequencies, and access methods. Map the data flows that need to converge in the warehouse.
Design the warehouse schema and semantic models based on your analytics requirements. Define dimensions, facts, and business metric calculations with stakeholder sign-off.
Build ETL/ELT pipelines for each source system. Implement data quality checks, transformation logic, and incremental refresh strategies.
Validate warehouse data against source systems. Reconcile counts, totals, and key metrics. Go live when data accuracy meets defined thresholds.
Deploy pipeline monitoring, data freshness alerts, and quality dashboards. Ongoing maintenance as source systems change or new data sources are added.
Frequently Asked Questions
Every engagement starts with an assessment.
Not a proposal. Not a sales call. We tell you what we find, not what you want to hear. The Launchpad assessment maps your operation before any software work begins.