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Advanced analytics demo
Automatic data validation and demand forecasting
This is how a monthly planning process works when data delivery, validation, forecasting and reporting are automated end to end. Try it with one of the three sample files.
Data that validates itselfStructure, catalog, integrity and statistical rules before a single number is loaded.
Clear answers for the analystRow, column and what to fix, instead of a technical error.
Forecasts with a confidence levelExpected range and observed error; no made-up numbers for new products.
- Python
- SQL
- BigQuery
- Cloud Run
- Pipelines
- Power BI
- Looker
- Generative AI for the summary
Simulated data. Figures, products, regions and files are fictitious and only illustrate how it works. They do not belong to any company.
- 1The file is delivered
- 2It validates itself
- 3Answer to the analyst
- 4Forecast available
Step 1
The analyst delivers the monthly file
They drop it in the usual folder; nothing changes in how they work. Pick one of these three cases to see what happens next.
Select a file to continue
Does your planning depend on files reviewed by hand?
A first conversation reviews how your data arrives today and which parts of the process can be validated, forecast and reported automatically.
Let's talk about your case