With a SFTP server integration, the customer is responsible for data accuracy and format

Dear Lucy will simply read the data as it is in the CSV file, minimizing risks of human errors and misinterpretations. 

Data Accessibility

The Dear Lucy integration service runs in AWS. All data should be accessible from the following IP addresses: 34.255.17.121, 34.246.213.238, 34.247.172.200 and 34.247.65.152.

Data Interpretation

Each row in a CSV or database is an independent unit of data, other rows do not affect how it is interpreted.

Initial Data

Initial data is fetched from the beginning of the previous year up to the current date. There should be a way to retrieve this range of data when needed, eg. if there have been significant changes to the contents of the data that require all of it to be re-imported.

Updates to Existing Data

Each unit of data should have a unique ID so that it can be updated with new information when needed. There should be a method to fetch the latest changes to data. 

It is important to consider that Dear Lucy dashboard fetches updated data from the same file regularly, but only reads the current state of the data.

In other words, if past data has been changed or deleted, there is no way for Dear Lucy’s system to capture those changes, since there is no log of changes. This is the case particularly for CSV files or time based structures.

Deletion of Existing Data

Deleted data in the source system should also be marked as deleted in the transferred data. This should use the same unique ID which is used to update existing data.

Data Format

Event-based template

Each data unit is an individual record, eg. a financial transaction or sales case and is not aggregated. Each data unit can have additional dimensions similar to aggregated data. This format is suitable when detailed information about a metric is required, eg. a drill down table showing individual sales for the current month.

Example

Download the attachment below to see an example of the required data format.