Data-Architect Exam Dumps : Salesforce Certified Platform Data Architect (Plat-Arch-201)

 Skinny tables are custom tables that contain frequently used fields from a standard or custom object. They are used to improve performance by reducing the number of database joins required for queries. Skinny tables have the following characteristics1:

They do not include soft-deleted records, which means they only contain active records and save space.

They avoid resource intensive joins by storing data from multiple objects in one table, which reduces the query time and complexity.

Their tables are kept in sync with their source tables when the source tables are modified, which ensures data consistency and accuracy.

Before replicating the data from Heroku Postgres to Salesforce, the data architect should consider the following factors:

Whether the data is a driver of key processes implemented within Salesforce. For example, if the data is used for workflows, triggers, or validation rules, it should be replicated to Salesforce.

Whether there is a tight relationship between order data and an enterprise resource planning (ERP) application. For example, if the order data needs to be synchronized with the ERP system, it should be replicated to Salesforce.

The selection of the tool required to replicate the data. For example, Heroku Connect can be used to bi-directionally sync data between Heroku Postgres and Salesforce

 Engaging with executive sponsorship to assess enterprise data strategy and goals, and engaging with business units and IT to assess current operational systems and data models are two first steps that would be appropriate for UC to initiate an assessment of data architecture. These steps will help to understand the current state of data management, the business needs and expectations, and the gaps and opportunities for improvement. Engaging with IT program managers to assess current velocity of projects in the pipeline, and engaging with database administrators to assess current database performance metrics are not relevant steps for assessing data architecture, as they are more related to project management and technical performance.