📡 Data Concerns

The data concerns tab helps you see if there are any data issues that may impact the read of your model. Every week Recast ingests your latest data and refreshes the model. If the model detects any issues, you will receive an email alerting you of this so that you have the opportunity to correct any errors.

This tab contains:

• A table of all the errors and warnings regarding your latest refresh

• A table of the date through which your model was last refreshed, the date through which your model was most recently refreshed

• A table of all the rows in your dataset with revisions to the channel spend

If you see any errors, this will stop your model from running until you are able to correct the errors detected. Warnings will not stop your refresh but may impact the read you get from the model. Recast recommends you flag any issues with your internal point of contact for data. Once you have corrected your data, you can head to the refresh tracker to schedule a new refresh.

Some common issues and how to resolve them are:

Historical revisions in channel spend: This means that there were changes to the amount you reported to spend in a channel. Recast received spend data that when compared to a previous data set, was different. This could mean that we initially received incomplete data or that some of your data is missing.

Historical revisions in KPI: This means that with the new data ingest, there were changes to the KPI you reported compared to your previous data ingest. This could mean that we initially received incomplete data or that some of your data is missing. Ex. You reclassified how you report “returns” in your sales data, causing historical data to change

Unusually low KPI values: This means that the KPI we are modeling looks suspiciously low during the period of the new data. This could be because all your data wasn’t fully in. Ex. sales from Target were reported but sales from Walmart were missing.

Critical errors that will cause your refresh to fail include:
Missing data for certain dates
Duplicate dates detected
Recent data is not newer than historical data

Date Ranges for Model Data
This box shows you a breakdown of when the data was last refreshed, what date the current refresh's data is through, and what date the prior refresh's data was through. You can use this to check that your model will be updated through the day you expect. Using the tabs you can toggle between these dates for each of your models.

Historical revisions detected in channel spend
Finally, you can see a table of all the revisions in channel spend detected in your most recent dataset that you provided for your most recent refresh. This table shows the date on which the data is different from the previous dataset, the channel for which spend was different, the previous spend reported, the currently reported spend and the difference between the two. This can help you identify what is causing the revisions in your data.

Sometimes, the current data is correct. In this case, just keep an eye out for potential ways in which this could impact your previous forecasts or optimizations as these might have under or over predicted due to the previously incorrect data.

How to resolve data issues

Before you click the refresh button or schedule your refresh, make sure that your data does not have any data quality issues. Data quality issues can cause model instability. To check for any issues:

Check the problematic data points indicated in the table
Check to make sure you uploaded a complete dataset
Dig into why you may be seeing historical revisions by looking for data entry errors or delays in when data comes from your vendors.