Salesforce Data-Architect Exam With Confidence Using Practice Dumps

The three key steps that a data architect should take when merging data from multiple systems into Salesforce are:

Analyze each system’s data model and perform gap analysis. This step involves understanding the structure and meaning of the data in each system, identifying the common and unique data elements, and mapping the data fields between the systems. This step also involves assessing the quality and consistency of the data, and identifying any data cleansing or transformation needs.

Utilize an ETL tool to merge, transform, and de-duplicate data. This step involves using an ETL tool to connect to the source systems, extract the data, apply any data transformations or validations, and load the data into Salesforce. This step also involves applying de-duplication rules or algorithms to avoid creating duplicate records in Salesforce.

Work with stakeholders to define record and field survivorship rules. This step involves collaborating with the business users and owners of the data to determine which records and fields should be retained or overwritten in case of conflicts or discrepancies. This step also involves defining the criteria and logic for record and field survivorship, and implementing them in the ETL tool or in Salesforce.

Creating new fields to store additional values from all the systems is not a key step, but rather a possible outcome of the gap analysis. It may not be necessary or desirable to create new fields for every value from every system, as it may result in redundant or irrelevant data. Installing a 3rd party AppExchange tool to handle the merger is not a key step, but rather a possible option for choosing an ETL tool. It may not be the best option depending on the requirements, budget, and preferences of the organization.

 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.

The two features that a data architect should recommend to share records between Salesforce orgs are:

Change Data Capture (CDC): This is a feature that publishes change events for changes in Salesforce records, such as create, update, delete, and undelete operations. Change events can be subscribed by external systems or other Salesforce orgs using various tools, such as Platform Events, Streaming API, or CometD. CDC can help keep data in sync between Salesforce orgs in near real time89.

Salesforce to Salesforce (S2S): This is a feature that allows sharing records and related data with other Salesforce orgs that you partner with. You can choose which records and fields to share, and which orgs to share with. You can also accept updates from the other orgs to keep the data consistent10.

Salesforce Connect is not a good feature to share records between Salesforce orgs because it is intended for integrating external data sources with Salesforce using external objects. Federation Search is not a good feature to share records between Salesforce orgs because it is intended for searching across multiple Salesforce orgs without sharing data.