Inventory Ledger Report - Detailed View
Inventory Ledger Report - Detailed View can be used to request and retrieve tab-delimited flat file report. It is used to analyze your inventory movements to and from Amazon fulfillment centers, including products that are sold, returned, removed/disposed, damaged, lost, and found. You can view all historical movements of your inventory for 18 months in this report.
Read more about this end-point here
Configuring the Credentials
Select the account credentials which has access to relevant Amazon Seller Central data from the dropdown menu & Click Next
Data Pipelines Details
- Data Pipeline
Select Inventory Ledger Report - Detailed View from the dropdown
Select the dimensions you would like to fetch from the Amazon Seller Performance platform. You can click on View Schema anytime to see the schema of the table being created.
|Each of the selected dimension / metric will create one or more columns in the database table in the destination warehouse.|
This refers to the manner in which data will get updated in the data warehouse, with 'Delete' selected, the data will be upserted (only new records or records with changes) and with 'Append' selected, all data fetched will be inserted. Selecting 'Replace' will ensure the table is dropped and recreated with fresh data on each run. Recommended to use "Upsert" option unless there is a specific requirement.
Default Value: UPSERT
No of Days
Number of days for which you wish to get the data in each run.
Integer value (Recommended value 30)
Scheduling specifies the frequency with which data will get updated in the data warehouse. You can choose between Manual Run, Normal Scheduling or Advance Scheduling.
- Manual Run
If scheduling is not required, you can use the toggle to run the pipeline manually.
- Normal Scheduling
Use the dropdown to select an interval-based hourly, monthly, weekly, or daily frequency.
- Advance Scheduling
Set schedules fine-grained at the level of Months, Days, Hours, and Minutes.
Detailed explanation on scheduling of pipelines can be found here
Dataset & Name
- Dataset Name
Key in the Dataset Name(also serves as the table name in your data destination).Keep in mind, that the name should be unique across the account and the data source. Special characters (except underscore _) and blank spaces are not allowed. It is best to follow a consistent naming scheme for future search to locate the tables.
- Dataset Description
Enter a short description (optional) describing the dataset being fetched by this particular pipeline.
Choose the events for which you’d like to be notified: whether "ERROR ONLY" or "ERROR AND SUCCESS".
Once you have finished click on Finish to save it. Read more about naming and saving your pipelines including the option to save them as templates here
Still have Questions?
We’ll be happy to help you with any questions you might have! Send us an email at firstname.lastname@example.org.
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