Salesforce Data-Architect Exam With Confidence Using Practice Dumps

Exporting in multiple batches and using PK Chunking are two steps that can help correct the issues with exporting large volumes of Order records using Informatica Cloud Loader. Exporting in multiple batches can reduce the load on the system and avoid timeouts or errors. Using PK Chunking can split a large data set into smaller chunks based on the record IDs and enable parallel processing of each chunk.

According to the Data Modeling unit on Trailhead, some of the key actions that should be done when data modeling in Salesforce are identifying data elements, mapping legacy data, and implementing legacy data model. The unit states that “Before you start creating objects and fields in Salesforce, you need to identify the data elements that you want to store and work with. … Next, you need to map your legacy data to Salesforce objects and fields. … Finally, you need to implement your data model in Salesforce by creating custom objects and fields using declarative tools or Metadata API.” Therefore, these are the correct actions for migrating a legacy client server app to Salesforce.

 The Data Architect should consider the limitations on Org data storage and the Bulk API limitations on picklist fields when denormalizing the data model into a single Transaction object with a Branch Office picklist. The Org data storage limit is the total amount of data that can be stored in a Salesforce Org, and it depends on the edition and license type of the Org1. The Bulk API limit on picklist fields is the maximum number of values that can be imported or exported using the Bulk API, and it is 1,000 values per picklist field2. These limitations could affect the performance and scalability of the data model, and the Data Architect should plan accordingly.