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| Section | Weight | Objectives |
|---|---|---|
| Data Modeling/Database Design | 25% | - Describe the implications of LDV on data modeling - Explain the usage of external objects - Describe the options and considerations for Large Data Volumes (LDV) - Describe the considerations when designing a data model for Salesforce |
| Data Governance | 10% | - Describe the elements of a data governance framework - Describe the considerations for data quality - Describe the considerations for data classification |
| Large Data Volumes | 20% | - Describe the features and best practices for LDV - Describe the implications of LDV on data modeling - Describe the considerations for Large Data Volumes (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 |
| Salesforce Data Management | 25% | - Describe the considerations for data migration - Describe the implications of LDV on data management - Describe the considerations for data governance - Describe the considerations for data archival |
| Master Data Management | 5% | - Describe the considerations for a Master Data Management strategy - Describe the methods for aligning data across systems |
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NEW QUESTION # 78
A shipping and logistics company has created a large number of reports within Sales Cloud since Salesforce was introduced. Some of these reports analyze large amounts of data regarding the whereabouts of the company's containers, and they are starting to time out when users are trying to run the reports. What is a recommended approach to avoid these time-out issues?
Answer: B
Explanation:
Improving reporting performance by replacing the existing reports in Sales Cloud with new reports based on Analytics Cloud can avoid the time-out issues by leveraging the power and scalability of Analytics Cloud. Analytics Cloud can handle large volumes of data and provide faster and more interactive reports than Sales Cloud.
NEW QUESTION # 79
UC is rolling out Sales App globally to bring sales teams together on one platform. UC expects millions of opportunities and accounts to be creates and is concerned about the performance of the application. Which 3 recommendations should the data architect make to avoid the data skew? Choose 3 answer
Answer: A,C,E
Explanation:
Data skew occurs when a large number of child records are associated with a single parent record, or when a single user owns a large number of records. This can cause performance issues and lock contention. To avoid data skew, the data architect should limit assigning one user
10,000 records ownership, limit associating 10,000 opportunities to one account, and limit associating 10,000 records looking up to the same record
NEW QUESTION # 80
Universal Containers (UC) owns several Salesforce orgs across a variety of business units. UC management has declared that it needs the ability to report on Accounts and Opportunities from each org in one place. Once the data is brought together into a global view, management would like to use advanced Al-driven analytics on the dataset. Which tool should a data architect recommend to accomplish this reporting requirement?
Answer: D
Explanation:
According to this article, Einstein Analytics for multi-org can help UC to report on accounts and opportunities from each org in one place. It can also provide advanced AI-driven analytics on the dataset using Einstein Discovery.
NEW QUESTION # 81
Universal Container has a Sales Cloud implementation for a sales team and an enterprise resource planning (ERP) as a customer master Sales team are complaining about duplicate account and data quality issues with account data. Which two solutions should a data architect recommend to resolve the complaints?
Answer: A,D
Explanation:
Integrating Salesforce with ERP and making ERP the system of truth (option B) and implementing a de-dupe solution and establishing account ownership in Salesforce (option D) are the two solutions that a data architect should recommend to resolve the complaints. Option B ensures that account data is consistent and accurate across both systems, while option D prevents duplicate records and clarifies who owns each account in Salesforce.
NEW QUESTION # 82
Universal Containers is planning out their archiving and purging plans going forward for their custom objects Topic__c and Comment__c. Several options are being considered, including analytics snapshots, offsite storage, scheduled purges, etc. Which three questions should be considered when designing an appropriate archiving strategy?
Answer: C,D,E
Explanation:
The three questions that should be considered when designing an appropriate archiving strategy are: If reporting is necessary, can the information be aggregated into fewer, summary records?
Will the data being archived need to be reported on or accessed in any way in the future? Are there any regulatory restrictions that will influence the archiving and purging plans? These questions are important because they help determine the scope, frequency, and method of archiving and purging data from Salesforce. For example, if reporting is necessary, then summary records or analytics snapshots can be used to store aggregated data and reduce the number of records that need to be archived. If the data being archived needs to be accessed in the future, then offsite storage or external objects can be used to retain the data and make it available on demand. If there are any regulatory restrictions, such as GDPR or HIPAA, then the archiving and purging plans need to comply with them and ensure data security and privacy
NEW QUESTION # 83
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