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 · 🆘 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.

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

Most "AI analytics" tools generate numbers from LLM guesses. OWOX AI Insights run pre-approved SQL your analyst manages. AI helps with narrative prose, not the numbers. Every value is the result of a deterministic SQL query — not a prediction. Backed by patented technology.

Why it matters:

• Specialized legal AI tools hallucinate 17%+ of the time; general-purpose chatbots hit 58–82% (Stanford HAI, 2025)
• 46% of developers actively distrust AI tool accuracy (Stack Overflow Developer Survey, 2025)
• EU AI Act (effective August 2025) mandates traceable logic on every AI insight used in significant decisions — fines up to €35M

2. No Semantic Layer Required

"The semantic layer is fragmented between tools, suffers from vendor lock-in and requires duplicate encoding of business logic that is costly to maintain... making adoption economically unviable for many firms."

— Semantic Layer Substack

Skip the 6–12 month semantic layer implementation. Plug in your existing SQL and ship. Business users get self-service in minutes, not quarters.

Why it matters:

• Production-ready semantic layer typically take 6–12 months for enterprise teams (Datacoves, 2026)
• Only 27% of teams plan to increase semantic layer investment (dbt Labs State of Analytics Engineering, 2025)
• Of the 30% using AI to consume data via natural language, two-thirds do so with vanilla SQL generation — not via a semantic layer

3. Data Stays in Your Warehouse

"I didn't get an error message — instead I got a column that is entirely blank. No zeroes, just blank all the way down."

— Supermetrics customer, Community Forum, July 2025 (after Meta cut historical data access)

Your data never leaves your infrastructure. Once normalized into your warehouse, it stays — immune to upstream API deprecations. Open-source core means no vendor lock-in.

Why it matters:

• Meta cut historical data on unique-count fields to 13 months and removed 7/28-day attribution windows entirely (Supermetrics docs, Jan 2026)
• 53.7% of CDOs serve less than 3 years; boards hold data leaders personally accountable for compliance and vendor risk (MIT Sloan, 2025)

Who Is OWOX For?

| | Data Analysts | Business Users | C-Suite | |---|---|---|---| | Problem | Buried in a reporting backlog — tickets, CSVs, one-off dashboards | Wait days for "just one more column" or trust ChatGPT with company numbers | Need AI-era throughput but can't afford hallucinated numbers at board level | | OWOX gives you | Define once, publish everywhere. Full SQL audit trail. Stay in control. | Self-serve from a governed data mart library in Google Sheets — no SQL, no tickets | Visible value in weeks. Auditable accuracy. No vendor lock-in. Open-source core. |

🚀 What You Can Do

• Create a Data Mart Library — Bring together data from your warehouse (BigQuery, Snowflake, Redshift, Athena, Databricks), APIs, or spreadsheets into fast, reusable artifacts
• Deliver Trusted Data Anywhere — One published data mart feeds Google Sheets, Looker Studio, Slack, email, and more — simultaneously, same numbers everywhere
• Automate Everything — Advanced scheduler refreshes both data marts and exports, fully automated from a single place
• Get AI Insights Without Hallucinations — AI drafts narrative reports from your analyst-approved SQL. Every number is traceable. Delivered to Slack, Teams, or email.

🛠 Quick Start

OWOX Data Marts can be run just about anywhere in minutes. Here’s how to get started locally on your machine:

(1) Install Node.js 22.22.0+ download

(2) Install OWOX Data Marts

npm install -g owox

(3) Start locally

owox serve

(4) Open 🎉

Live in under 5 minutes. For Docker and cloud deployment options, see the Quick Start Guide.

🗣️ What People Are Saying

*"Connected BigQuery, set up 37 data marts, built a data model and had live reports in Sheets in under 15 minutes.

*"We migrated 200+ reports from Looker to OWOX Data Marts. Our team now self-serves without filing a single Jira ticket.

"75% of CDAOs who fail to demonstrate AI's positive impact will be reassigned or removed from the C-suite by 2027."

— Gartner, via TechRadar, November 2025

🔌 Available Connectors

Open-source data connectors that pull from any API — zero external tools, no credential sharing, fully customizable.

Data Sources

| Name | Status | Links | | ------------------------------- | ---------------- | ----------------------------------------------------------------------------------- | | Bank of Canada | 🟢 Public | Get started | | Criteo Ads | 🟢 Public | Get started | | Facebook Ads | 🟢 Public | Get started | | GitHub | 🟢 Public | Get started | | Google Ads | 🟢 Public | Get started | | LinkedIn Ads | 🟢 Public | Get started | | LinkedIn Pages | 🟢 Public | Get started | | Microsoft Ads (former Bing Ads) | 🟢 Public | Get started | | Open Exchange Rates | 🟢 Public | Get started | | Open Holidays | 🟢 Public | Get started | | Reddit Ads | 🟢 Public | Get started | | Shopify | 🟢 Public | Get started | | TikTok Ads | 🟢 Public | Get started | | X Ads (former Twitter Ads) | 🟢 Public | Get started | | Hotline | ⚪️ In Discussion | Discussion | | Google Business Profile | ⚪️ In Discussion | Discussion |

Data Warehouses

| Name | Status | Links | | --------------- | --------- | ------------------------------------------------------------------- | | Google BigQuery | 🟢 Public | Readme | | AWS Redshift | 🟢 Public | Readme | | AWS Athena | 🟢 Public | Readme | | Snowflake | 🟢 Public | Readme | | Databricks | 🟢 Public | Readme |

If you find an integration missing, you can share your use case and request it in the discussions or build your own.

How it works

1. Analysts define data marts using SQL, existing tables/views, or connectors
2. OWOX governs — ownership, descriptions, aliases, join keys, access controls, and scheduling
3. Business users consume — browse the data mart library in Google Sheets, pick columns, apply filters, get live data
4. AI Insights narrate — pre-approved SQL generates numbers; AI writes the prose; delivered to Slack, Teams, email

🧑‍💻 Contribute

We're building this with the community, not just for it.

• Read the Contributor Guide
• Check open Issues
• Join Discussions

📌 License

OWOX Data Marts is free for internal or client use, not for resale in a competing product. Dual-license model:

• Connectors (packages/connectors) — MIT License
• Platform (all other files) — ELv2 License
• Enterprise features — Enterprise License (files in apps/backend/src/data-marts/data-destination-types/ee or containing .ee. in the filename)

Star this repo if OWOX saves your team from the reporting backlog.