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| Section | Weight | Objectives |
|---|---|---|
| Data Modeling/Database Design | 25% | - Describe the options and considerations for Large Data Volumes (LDV) - Describe the implications of LDV on data modeling - Describe the considerations when designing a data model for Salesforce - Explain the usage of external objects |
| Master Data Management | 5% | - Describe the considerations for a Master Data Management strategy - Describe the methods for aligning data across systems |
| Large Data Volumes | 20% | - Describe the implications of LDV on data modeling - Describe the features and best practices for LDV - Describe the considerations for Large Data Volumes (LDV) |
| Data Migration | 15% | - Describe the considerations for data migration - Describe the tools and best practices for data migration - Describe the implications of data migration on data quality |
| Salesforce Data Management | 25% | - Describe the considerations for data migration - Describe the considerations for data governance - Describe the considerations for data archival - Describe the implications of LDV on data management |
| Data Governance | 10% | - Describe the considerations for data quality - Describe the elements of a data governance framework - Describe the considerations for data classification |
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NEW QUESTION # 271
UC has a requirement to migrate 100 million order records from a legacy ERP application into the salesforce platform. UC does not have any requirements around reporting on the migrated data.
What should a data architect recommend to reduce the performance degradation of the platform?
Answer: D
Explanation:
Implementing a custom big object to store the data is the best recommendation to reduce the performance degradation of the platform, as it allows storing large volumes of data that do not need real-time access or reporting. Custom big objects can be defined using metadata API or developer console, and support up to 1 billion records per object. Creating a custom object or using the standard order object would consume a lot of storage space and impact the performance of queries and reports. Using a standard big object defined by salesforce would not be applicable for order records, as standard big objects are predefined for specific use cases such as audit trails or field history.
NEW QUESTION # 272
UC has millions of case records with case history and SLA data. UC's compliance team would like historical cases to be accessible for 10 years for Audit purpose. What solution should a data architect recommend?
Answer: C
Explanation:
The best solution to store historical cases for 10 years for audit purpose is to use a custom Big object to store archived case data. Big objects are a type of custom object that can store massive amounts of data on the Salesforce platform without affecting performance or storage limits. They also support point-and-click tools, triggers, and Apex code. Big objects can be used for archiving historical data that needs to be retained for compliance or analytics purposes. Archiving case data using Salesforce Archiving process is not a good option because it only supports archiving cases that are closed for more than one year, and it does not allow customizing the archival criteria or accessing the archived data via Apex or APIs. Purchasing more data storage to support case object is expensive and may impact performance. Using a custom object to store archived case data is not scalable and may consume a lot of storage space.
NEW QUESTION # 273
Universal Containers (UC) is implementing its new Internet of Things technology, which consists of smart containers that provide information on container temperature and humidity updated every 10 minutes back to UC. There are roughly 10,000 containers equipped with this technology with the number expected to increase to 50,000 across the next five years. It is essential that Salesforce user have access to current and historical temperature and humidity data for each container. What is the recommended solution?
Answer: A
Explanation:
The recommended solution for Universal Containers (UC) to implement its new Internet of Things technology is to create a new Container Reading custom object with a master-detail relationship to Container which is created when a new measure is received for a specific container.
Implement an archiving process that runs every hour. This solution would allow UC to store and access current and historical temperature and humidity data for each container on Salesforce, and use reports and dashboards to analyze it. However, since UC expects a large volume of data over time, they should implement an archiving process that moves data off-platform after a certain period of time to avoid hitting the Org data storage limit and maintain optimal performance. The other options are not recommended, as they would either not store the historical data on Salesforce, or create too many custom fields on the Container object that could impact performance and usability.
NEW QUESTION # 274
Universal Containers has defined a new Data Quality Plan for their Salesforce data and wants to know how they can enforce it throughout the organization. Which two approaches should an architect recommend to enforce this new plan? Choose 2 answer
Answer: A,D
Explanation:
Scheduling a weekly dashboard displaying records that are missing information to be sent to managers for review and using Workflow, Validation Rules, and Force.com code (Apex) to enforce critical business processes are two approaches that an architect should recommend to enforce the new Data Quality Plan for UC's Salesforce data. Scheduling a weekly dashboard can provide a regular and visual way of monitoring the data quality and identifying any gaps or issues that need to be addressed by the managers or users. Using Workflow, Validation Rules, and Apex can provide various ways of enforcing data quality standards and business logic by automating actions, displaying error messages, or executing custom code when users create or edit records. The other options are not suitable or helpful for enforcing the Data Quality Plan, as they would either not provide real-time feedback, not prevent data quality issues, or not leverage the capabilities of Salesforce
NEW QUESTION # 275
Northern Trail Outfitters (NTO) has implemented Salesforce for its sales users. The opportunity management in Saiesforce Is implemented as follows:
1. Sales users enter their opportunities in Salesforce for forecasting and reporting purposes.
2. NTO has a product pricing system (PPS) that is used to update the Opportunity Amount field on opportunities on a daily basis.
3. PPS is the trusted source within NTO for Opportunity Amount.
4. NTO uses Opportunity Forecast for its sales planning and management.
Sales users have noticed that their updates to the Opportunity Amount field are overwritten when PPS updates their opportunities.
How should a data architect address this overwriting issue?
Answer: A
Explanation:
Changing Opportunity Amount field access to Read Only for sales users field-level security (option C) is the best way to address the overwriting issue, as it prevents sales users from updating the field that is controlled by PPS, and ensures data consistency and accuracy.
NEW QUESTION # 276
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