Overview

Preczn offers various methods for retrieving transaction data for analytical purposes. Designed to assist platforms in transferring or ingesting both historic and real-time transaction data, this guide aims to facilitate your integration with data analytics tools such as Snowflake, Tableau, or PowerBI.

Retrieving Historic Data

List Transaction API

Overview

The List Transactions API endpoint can be used to return the full json body of historic transactions. Results are paginated in groups of 50 transactions.
You may wish to use the List Transaction API is conjunction with services like AWS Lambda, scheduled jobs, or other ETL services to facilitate the extraction.

Use Cases

Historic backfill of transaction data
Time bound data extraction (hourly, daily, weekly, etc) data extraction.

How to Implement

Please review the full API details at List Transactions in the API Guide.
The API supports query parameters of both a date range and merchant ID if you wish to narrow transaction results.

Transaction Export

Overview

The Transaction Export feature enables users to extract a large volume of transactions by generating and downloading CSV files containing transaction data. Transactions must fall within a specified time range and can optionally be limited to specific merchants; otherwise, all transactions for the platform within that time range will be included.

The data in the CSV file mirrors the transaction responses, with fields that would have appeared in the JSON now represented as distinct columns.

Use Cases

Historic backfill of transaction data
Time bound data extraction data extraction on a larger range (weekly/monthly/quarterly)

How to Implement

Navigate to the 'Transaction Export' page via the 'Transactions' section in the sidebar menu to initiate and download transaction CSVs.
To start a new export, specify a date range for the transactions. You may optionally select a specific merchant from a dropdown list.
Upon clicking 'submit,' the requested export will display as 'Pending' in the table. This will be where you later retrieve the data.
Processing time will vary based on the size of the data set being pulled. When the data pull is complete, an email notification will be sent notifying the CSV is ready for download
The CSV can be downloaded from the same row in the Transaction Export Files Table.

Considerations:

The processing time for transaction data will vary depending on several factors, including the size of the date range, your transaction volume, and whether the extract includes transactions from all platform merchants or just a specific one. If you haven't received results within 24 hours for a large data set, please contact Preczn for assistance.
The download of the resulting file may take some time depending on the number of transactions requested. Please select 'download' and then leave the browser on the Transaction Export screen.

Retrieving Real-Time Data

Transaction Webhooks

Overview

Transaction webhooks can be employed to receive real-time updates on transaction events. This is especially important if you're using a connection with an asynchronous approval process. Webhooks can relay the complete lifecycle of a transaction, from its 'Pending' status to its eventual 'Declined' or 'Approved' state.

Webhooks can also be configured to deliver information to systems other than your application. You may choose to leverage services like AWS Lambda, web servers, or other ETL services to facilitate data extraction.

Use Cases

Real time transaction data extraction including updates to existing Pending Transactions

How to Implement

Webhooks will include the full body of the original or updated transaction. Please review our webhook documentation for configuration and ingestion:

Logging Transaction Responses

Overview

Many platforms opt to extract transaction data by logging the response from the transaction API. This approach offers the advantage of immediate availability, making it highly conducive for ETL (Extract, Transform, Load) processes. By capturing the API response in real-time, platforms can quickly initiate data transformation and loading activities, thereby streamlining the overall data management workflow.

How to Implement

To develop the most effective data extraction and ETL (Extract, Transform, Load) strategy using the JSON response, it's crucial to coordinate closely with your development team. Discuss the specific requirements, constraints, and goals to ensure that the strategy aligns with your platform's needs.

Use Cases

Real time transaction data extraction

Limitations and Considerations

If your platform utilizes a connection with an asynchronous approval process, it's advisable to make use of transaction webhooks to receive real-time updates on pending transactions.