Some of you might wonder, how can PlanIQ leverage related datasets that are external to company's data, for example custom holidays, demographic data, or projected industry growth. This article explains how such datasets can be added to your related data module and leveraged by PlanIQ.

We will use Kaggle's Favorita dataset which is an open source dataset with sample of retail data from the Corporación Favorita Grocery chain.

Setting up the dataset for PlanIQ ingestion

The dataset contains, among other things, a file with daily oil price and it can be assumed that Ecuador's economical health is dependent to shocks in oil prices. You will note that this file has the time dimension and oil price, but does not have the item / SKU dimension that is required by related dataset in PlanIQ. This is the format of the file with oil prices:

Our related data module is dimensionalized by time and SKU-store combination.

In order to be able to use the old index data, we need to make sure that Anaplan does not require SKU-store as a dimension for the oil price.

As you import the oil price data, you don't need to provide mapping to SKU-store combination.

You will notice that this method not only allows you to skip creation of SKU-store combinations but also saves a great deal of workspace:

Let us know what types of data you would like to leverage for your forecasts.