Project details

The main objectives of this development are the processing of more data and interaction with a bucket on the Amazon S3. In addition, the application should be as flexible and customizable as possible. Finally, this development should be able to build a CSV file on a scheduled basis that containing any data by user requirements or handle the downloaded file from the Amazon S3 as required by user. The FeedVisor team built a chain of events "to improve the lead generation and sales processes using more data, machine learning and data models". And the S3 bucket is used to exchange data between different systems, one of which is Salesforce. A few important events on the Salesforce side: Import data from the bucket and update Salesforce records by the unique identifiers or external keys. Export Salesforce records and upload them to the specified bucket as CSV file. Retrieve data from the Marketo, then upload to the specified bucket as CSV file. In addition to the basic events on the Salesforce side: Implementation of automatic file management. The order of the main events. Each of these events contained processing of more data and interaction with Amazon S3. "Because Apex runs in a multitenant environment, the Apex runtime engine strictly enforces limits to ensure that runaway Apex code or processes don’t monopolize shared resources. If some Apex code exceeds a limit, the associated governor issues a runtime exception that cannot be handled." Considering the above, special requirements for us were the creation of a process that will resistant to errors. The process, which prevents the problems associated with platform limitations. The process that can tell the user that the system is configured incorrectly. Also our goal was to make the complex process easy to use and understandable for the user. And to carry out this goal, the development contains a logging system and a system for sending notifications to the user at each step.