Documentation

‍Improvado can ingest your data by setting up an email address created specifically for your data set.

Requirements and preconditions

If your data provider fits the following conditions, we can easily create this email integration for you:

1. Data should be in one of the following formats:

• tsv, csv, xls(x) files
• compressed versions (zip, gzip, tar.gz archives)

2. You should sent your data as:

• file attachment
• valid download link in email body

3. Data set should be presented as a flat table:

• one table per file
• column names in the first row
• no tabulation
• no data hierarchy
• no images

4. Data structure (field names, field order and data types) should NOT be changed without warning

5. Your data provider should be able to send reports via email automatically and regularly‍‍

How to setup an email integration

Step 1. Contact our technical support and tell us what you want:

• which data source do you need to connect?
• an example of your data frame is very helpful (for uncommon report types or data formats it is necessary
• how often should this data be refreshed (typically - on a daily basis)?
• update policy:
  - should we append, update or replace data?
  - in case of an update or replacement, you should specify the key column

Step 2. Get a confirmation from Improvado that we can ingest your data or instructions on what needs to be changed in order to make it possible.

Step 3. Send test data to a pre-determined email address

• typically we create an email by the following scheme: reports+{business name}+{report type}+{platform}@improvado.io

Step 4. We will confirm whether we have successfully loaded the data

Step 5. Schedule reports from your data platform using the email given.

That’s all! Your data platform sends us your data with the selected frequency and we do the rest of the job on our side.

Special options

In addition, we can offer the following options:

• one-time historical data download or reference data download if required for custom reports or data transformations
• client data analysis (for unstructured or atypical data formats) to select the best data loading method
  - in this case, examples of data set needed
• data update frequency changes (if necessary)
• report format or data structure update (if data source changes the set of fields available)