💄 BeautyCommerceOS

Autonomous Analytics & Enterprise Reasoning Benchmark

BeautyCommerceOS is a large-scale synthetic enterprise data warehouse designed to benchmark autonomous AI agents and analytics systems operating in realistic business environments.

It simulates the full lifecycle of a modern global beauty ecommerce company — from user behavior to financial reconciliation — including the ambiguity, inconsistency, and cross-functional complexity found in real enterprises.

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🧠 Why this dataset exists

Most datasets teach analysis on clean tables.

BeautyCommerceOS teaches something harder:

Cross-domain reasoning across a messy, real-world enterprise.

It is designed to evaluate whether AI systems can reason across:

• conflicting KPIs across departments
• delayed revenue recognition
• attribution uncertainty across marketing channels
• inventory and supply chain mismatches
• finance vs marketing reporting divergence
• experimentation interference effects

This makes it suitable for evaluating LLM agents, autonomous analysts, and decision intelligence systems.

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🏗️ Dataset Structure

The dataset follows a modern medallion warehouse architecture:

🟤 Bronze Layer (Raw Behavioral Data)

• sessions
• clickstream events
• anonymous users

⚪ Silver Layer (Conformed Dimensions)

• products
• SKUs
• brands
• suppliers
• warehouses
• identity mapping

🟡 Gold Layer (Business & Financial Truth)

• orders
• order_items
• payments
• refunds
• campaigns
• attribution
• inventory
• shipments
• invoices
• profit & loss (P&L)

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📊 Key Capabilities

BeautyCommerceOS supports evaluation of:

🧠 AI Agent Reasoning

• multi-step business question answering
• cross-table joins across domains
• causal inference under noisy signals

📈 Marketing Intelligence

• attribution modeling
• ROAS vs profit divergence
• influencer impact analysis
• channel cannibalization effects

🚚 Supply Chain Analytics

• stockout impact analysis
• fulfillment delay tracking
• warehouse performance comparison

💰 Financial Reconciliation

• revenue recognition delays
• finance vs marketing mismatches
• margin decomposition

🧪 Experimentation Analysis

• A/B test evaluation
• treatment contamination
• causal uplift estimation

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⚠️ Realism & Complexity

Unlike traditional synthetic datasets, BeautyCommerceOS intentionally includes:

• inconsistent attribution signals
• delayed financial reconciliation
• missing or noisy event data
• KPI definition conflicts across teams
• operational distortions across systems

These are included to reflect real enterprise environments and enable robust evaluation of reasoning systems.

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🔍 Example Evaluation Tasks

BeautyCommerceOS can be used to evaluate systems on questions such as:

📈 Business Performance

• Why did revenue increase while profit declined?
• Which channels generate the lowest long-term customer value?

🧠 Attribution & Marketing

• Which attribution model best explains observed revenue?
• Are influencer campaigns profitable after refunds and returns?

🚚 Operations

• Which warehouses contribute most to fulfillment delays?
• How do stockouts impact downstream revenue loss?

💰 Finance

• Why do finance and marketing report different revenue figures?
• What is the true margin after operational adjustments?

🤖 AI Agent Benchmarking

• Can an autonomous agent reconcile conflicting KPIs across systems?
• Can it identify root causes across marketing, finance, and logistics?

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🚀 Intended Use

This dataset is designed for:

• autonomous agent evaluation
• LLM reasoning benchmarks
• analytics engineering practice
• causal inference research
• BI system testing
• data warehouse simulation
• decision intelligence systems

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🚫 Not Intended For

• real-world financial forecasting
• production decision-making
• regulatory reporting
• personal or sensitive data usage

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🔒 Synthetic Data Statement

All data in this repository is fully synthetic and generated programmatically.

No real users, transactions, or personally identifiable information are included.

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📦 Format

• Columnar storage: Parquet
• Architecture: Medallion (Bronze / Silver / Gold)
• Structure: Partitioned data warehouse
• Size: < 10 GB total

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📜 License

Licensed under CC BY 4.0.

You are free to:

• use
• modify
• redistribute
• build upon

with attribution.

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🏁 Vision

BeautyCommerceOS bridges the gap between:

• clean academic datasets
• and real-world enterprise complexity

It is designed to test whether modern AI systems can move beyond simple data analysis into true enterprise-level reasoning under ambiguity.