OWOX Data Marts
Your AI Reporting Data Analyst — Open Source
Stop shipping reports. Hire a reporting data analyst for each of the team members. OWOX Data Marts automates what reporting data analysts do — governed by data teams, consumed by business users with NO AI Hallycinations.
📘 Quick Start Guide · 📚 Docs · 🌐 Website · 💬 Slack · 🆘 Issues
✨ Why We Built This
Data analysts’ work means nothing unless business users can play with the data freely.
However, most self-service analytics initiatives fail because they compromise either the data analysts’ control or the business users’ freedom.
At OWOX, we value both:
- Data analysts orchestrate data marts defined either by SQL or by connectors to sources like Facebook Ads, TikTok Ads, and LinkedIn Ads.
- Business users enjoy trusted reports right where they want them — in spreadsheets or dashboards.
At OWOX, we believe data analysts shouldn’t have to waste time on CSV files and one-off dashboards. Business users shouldn’t have to be forced to use complex BI tools either.
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The Reporting Skills OWOX Automates
We analyzed 1,438 job postings for reporting data analysts at US ecommerce SMBs. Here's what companies pay $70–120k/yr for — and what OWOX handles out of the box:
| Skill | % of Job Listings | How OWOX Handles It | |-------|:-----------------:|---------------------| | Writing & maintaining SQL queries | ~95% | Create data marts from SQL, tables, views, or patterns — version-controlled and reusable | | Integrating data from multiple sources | ~85% | Open-source connectors (Facebook Ads, Google Ads, TikTok, Shopify, etc.) with zero data engineering | | Building & maintaining dashboards and reports | ~80% | Publish data marts to Google Sheets, Looker Studio, Slack, email — one source, many outputs | | Scheduling refreshes and timely delivery | ~70% | Built-in scheduler for data marts and exports — set once, runs forever | | Enabling stakeholder self-service | ~65% | Business users browse the data mart library in Google Sheets, pick columns, apply filters — no tickets | | Managing data access and permissions | ~40% | Ownership, context-based access, technical and business owners on every data mart |
What stays with your analysts (and becomes more valuable): data integrity validation, business logic mapping, variance diagnosis, metric definitions and standardization, stakeholder requests translation, and orchestrating AI-assisted workflows.
Why Teams Choose OWOX Over Alternatives
1. No AI Hallucinations. Ever
"Even one hallucination is too many in this line of work." — u/Cynot88, r/dataengineering