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| Section | Weight | Objectives |
|---|---|---|
| Data Modeling/Database Design | 25% | - Describe the implications of LDV on data modeling - Describe the options and considerations for Large Data Volumes (LDV) - Describe the considerations when designing a data model for Salesforce - Explain the usage of external objects |
| Data Governance | 10% | - Describe the considerations for data quality - Describe the considerations for data classification - Describe the elements of a data governance framework |
| Large Data Volumes | 20% | - Describe the implications of LDV on data modeling - Describe the considerations for Large Data Volumes (LDV) - Describe the features and best practices for LDV |
| Data Migration | 15% | - Describe the considerations for data migration - Describe the implications of data migration on data quality - Describe the tools and best practices for data migration |
| Master Data Management | 5% | - Describe the considerations for a Master Data Management strategy - Describe the methods for aligning data across systems |
| Salesforce Data Management | 25% | - Describe the considerations for data governance - Describe the considerations for data migration - Describe the considerations for data archival - Describe the implications of LDV on data management |
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NEW QUESTION # 151
Cloud Kicks has the following requirements:
- Their Shipment custom object must always relate to a Product, a
Sender, and a Receiver (all separate custom objects).
- If a Shipment is currently associated with a Product, Sender, or
Receiver, deletion of those records should not be allowed.
- Each custom object must have separate sharing models.
What should an Architect do to fulfill these requirements?
Answer: A
Explanation:
A required Lookup relationship ensures that the Shipment record must have a value for each of the three parent records, and also prevents the deletion of those parent records if they are referenced by a Shipment record. A Master-Detail relationship would not allow separate sharing models for each custom object, and a VLOOKUP formula field would not enforce the relationship or prevent deletion
NEW QUESTION # 152
Which API should a data architect use if exporting 1 million records from Salesforce?
Answer: B
Explanation:
Using Bulk API to export 1 million records from Salesforce is the best option. Bulk API is a RESTful API that allows you to perform asynchronous operations on large sets of data. You can use Bulk API to create, update, delete, or query millions of records in batches. Bulk API is optimized for performance and scalability, and it can handle complex data loading scenarios.
NEW QUESTION # 153
Which strategy reduces data skew risk?
Answer: D
Explanation:
Distributing ownership prevents skew.
NEW QUESTION # 154
UC is using SF CRM. UC sales managers are complaining about data quality and would like to monitor and measure data quality. Which 2 solutions should a data architect recommend to monitor and measure data quality? Choose 2 answer
Answer: B,D
Explanation:
Reviewing data quality reports and dashboards and installing and running data quality analysis dashboard app are two solutions that can help monitor and measure data quality. Data quality reports and dashboards can provide insights into the completeness, accuracy, and consistency of the data. Data quality analysis dashboard app is a free app from AppExchange that can help analyze and improve data quality by identifying duplicate, incomplete, or inaccurate records.
NEW QUESTION # 155
UC has migrated its Back-office data into an on-premise database with REST API access. UC recently implemented Sales cloud for its sales organization. But users are complaining about a lack of order data inside SF. UC is concerned about SF storage limits but would still like Sales cloud to have access to the data. Which design patterns should a data architect select to satisfy the requirement?
Answer: A
Explanation:
The best design pattern to satisfy the requirement of accessing order data from an on-premise database with REST API access without consuming SF storage limits is to use SF Connect to virtualize the data in SF and avoid storage limits. SF Connect is an integration tool that allows users to access and integrate data from external sources using external objects. External objects are similar to custom objects, except that the data resides in another system and is accessed in real time via web service callouts. SF Connect supports various adapters to connect to different types of external data sources, such as OData, cross-org, or Apex custom adapter. Migrate and persist the data in SF to take advantage of native functionality is not a good option because it would consume SF storage limits and require data synchronization between systems. Develop a bidirectional integration between the on-premise system and Salesforce is not a good option because it would be complex and costly to implement and maintain, and it would also consume SF storage limits. Build a UI for the on-premise system and iframe it in Salesforce is not a good option because it would not provide a seamless user experience and it would not allow users to search, report, or perform actions on the external data.
NEW QUESTION # 156
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