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Weather augmentation

Easy augmentation and backfill your business data with weather. Once you have one column with geo data, than it is very easy just by clicking to backfill this with historical, current and prediction data about weather at given geographical position.

The whole set up of recipe takes about 2 minutes.

Use case:

  • For you data science you need to correlate weather at given position/time with changes in your sales

  • Predictive analyses based on historical data from physical environment.

  • You have a theory that your telesales inflow correlates somehow with weather, but are not sure exactly how and with what part of weather. Is it temperature, humidity, changes in these or is it a bio ?

Grouped Histogram
You have several different data sets and need to find common areas.

Use case:
Grouping together age groups and most frequent shoppers in your shop.


Dependency of weight and MPG within the specific range of cars with different amount of valves.

Basket analyses/Next Order

Discover what your customers buy together. Predict what they are most likely buy next.

Goods that have the biggest potential to earn the biggest margin. Which combinations of these goods to offer together to what customers these are the questions that every business tries to solve. Although, there is not one easy answer and the reality can be more complex depending case to case, we have prepared a generic basket analyses that should satisfy most of the use cases and their first round of iteration.

Use case:

  • ecommerce shops aka food delivery

  • support tickets which go together when/what that means, etc.

  • when people come from train x at main station, how likely they are to log into wifi and what goods they usually buy at local shops ?