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Oxygen transforms how data teams work. Describe what you need in natural language and watch it come to life — ETL pipelines, semantic models, dashboards, and full data applications.
Data Apps
Full-stack applications powered by data
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Interactive visualizations and reports
Semantic Models
Define business logic and relationships
ETL Pipelines
AlphaExtract, transform, and load data across sources
Precision through the Large Analytics Model
Oxygen achieves deterministic precision through the Large Analytics Model (LAM) — a purpose-built system for data analytics based on the principle of entropy reduction.
Semantic and procedural context grounding every query in your business truth
Verifiable logic chains for traceable, deterministic results
Precise translation from natural language to analytics operations
Context
Semantic and procedural grounding
Reasoning
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Inference
Precise NL translation
Show me the factors influencing revenue growth
To identify the factors influencing revenue growth, it's important to analyze how various conditions—such as economic indicators (fuel prices, unemployment rate, CPI), seasonality (month, holiday weeks), and environmental factors (temperature)—correlate with and impact total sales over time.
Step-by-step plan:
- Check correlations between sales and major external factors: temperature, fuel prices, unemployment, and CPI.
- Compare sales during holiday weeks vs. non-holiday weeks.
- Observe sales trends across months (seasonality).
- Summarize the impact of these factors (correlations, seasonal patterns, holiday effects).
I'll query and synthesize results for:
- Correlation coefficients for each economic/environmental factor.
- Sales uplift during holidays vs. regular weeks.
- Revenue distribution by month.
Executing the relevant queries in parallel.
query_retail_analytics
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query_retail_analytics
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query_retail_analytics
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Here are the key factors influencing revenue growth, based on available data:
- Sales show notable variation by month, with peak revenues in July, April, and March. The lowest sales are typically in January and November.
- This suggests strong seasonal effects, possibly tied to holidays, back-to-school, and summer promotions.
- The average revenue during holiday weeks is higher ($1,122,888) than during non-holiday weeks ($1,041,256).
- There is a clear holiday sales lift: sales are 7.84% higher during holiday weeks versus non-holiday weeks.
- The correlation between temperature and sales is slightly negative (-0.064). This means hotter or colder weeks have a minor inverse relationship with sales, but it's not strong.
- The correlation between fuel prices and sales is nearly zero (0.009), suggesting very little direct impact.
- There is a weak negative correlation (-0.106) between unemployment rate and sales, implying that higher unemployment might slightly reduce sales, but it is not a dominant factor.
- The average values for context: temperature ~61°F, fuel price ~$3.36/gallon, unemployment ~8.0%, CPI ~171.58.
Summary:
- The biggest drivers of revenue growth are seasonality (time of year) and holidays.
- Economic factors like unemployment do have a small effect, while temperature and fuel prices have minimal influence on revenue in this dataset.
- Understanding these factors can inform marketing, promotions, and inventory strategies.
Would you like to see this visually (e.g., revenue by month chart or more detail on any specific factor)?
Ask any data question. Get precise, reasoned answers.
Oxygen agents analyze your data with the rigor of a senior analyst. They build step-by-step plans, execute parallel queries, and synthesize findings into actionable insights — all in seconds.
Automate analytics workflows with agentic procedures
Define complex multi-step analytics workflows as code. Oxygen procedures orchestrate SQL queries, transformations, and AI agents to produce deterministic, reproducible results every time.
Revenue Performance Analysis Report
Generated:
Executive Summary
Store Network Overview
- Total Stores: 45
- Status: Active
Revenue Performance
- Total Revenue: $673721898.11
- Average Revenue per Store: $14971597.49
- Average Weekly Revenue: $1046964.88
- Analysis Period: 14645 to 15639
Top Performing Stores
#1: Store 20
Build anything from ETL pipelines to data apps
Use natural language to build ETL pipelines, semantic models, interactive dashboards, and custom data applications. Oxygen generates production-ready code and deploys instantly.
Build me a data app looking at the correlations between factors that affect revenue and revenue
I built a data app to analyze the correlations between various factors (Temperature, Fuel Price, CPI, Unemployment, and Holidays) and store revenue, measured as Weekly Sales.
Here's what the app does:
- Shows a summary table of correlation coefficients between Weekly Sales and each factor.
- Plots average weekly sales against each factor (Temperature, Fuel Price, CPI, Unemployment) to visualize trends.
- Compares average revenue on holidays vs. non-holidays using a bar chart.
These visualizations and statistics help to quickly understand how much each factor correlates with revenue and reveal any potential patterns or relationships in the data.
I regenerated the data app revenue_correlations_app.app.yml with the following features and plots:
- A summary table showing the correlation coefficients between Weekly Sales and each factor (Temperature, Fuel Price, CPI, Unemployment, Holiday Flag).
- Bar chart comparing average weekly sales on holidays vs. non-holidays.
- Four line charts showing average weekly sales as a function of each factor:
- Temperature
- Fuel Price
- CPI
- Unemployment
This setup allows you to clearly see statistical relationships and trends between revenue and the influencing variables, providing both quantitative (correlation table) and visual insights (charts).
Revenue Correlation Analysis
This dashboard visualizes how various factors relate to store revenue (Weekly Sales) at Oxymart. Use the plots and summary table to explore the relationships.
Correlation Coefficients with Weekly Sales
| corr_temp | corr_fuel | corr_cpi | corr_unemployment | corr_holiday |
|---|---|---|---|---|
| -0.06 | 0.01 | -0.07 | -0.11 | 0.04 |
Average Weekly Sales: Holiday vs. Non-Holiday
Average Weekly Sales by Temperature
Average Weekly Sales by Fuel Price
Works with your stack. Batteries included.
Connect to your existing data warehouse, ingestion tools, and semantic layer. Or use Oxygen's built-in infrastructure for a zero-config experience.
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airapp (Data App)
Declarative and agent-first framework for building data apps
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Define metrics and dimensions once, use everywhere
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Automate complex analytics procedures using agents
airform (ETL Engine)
AlphaBuilt-in pipelines with incremental processing
airlake (Lakehouse)
AlphaServerless storage with open table formats
No external dependencies required
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