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| Section | Weight | Objectives |
|---|---|---|
| Data Integration | 15% | - ETL tools and data migration strategies - Handling locks and parallelism during migration - Sharing rules impact on data integration - Real-time vs batch integration patterns - API-based integration (REST, SOAP, Bulk API) |
| Data Modeling | 25% | - Indexing strategies - Big Objects and external objects - Large Data Volumes (LDV) design considerations - Skinny tables for performance optimization - Normalization and denormalization strategies |
| Data Governance | 20% | - Data quality standards and metrics - Data stewardship roles and responsibilities - Compliance and regulatory considerations - Data retention and archiving policies |
| Data Architecture | 20% | - Governor limits and bulk processing - Architecture patterns and design principles - Archiving and data lifecycle management - Performance tuning and optimization |
| Master Data Management | 20% | - Data cleansing techniques - Identity resolution - Data duplication and matching rules |
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NEW QUESTION # 138
US has released a new disaster recovery (DR)policy that states that cloud solutions need a business continuity plan in place separate from the cloud providers built in data recovery solution.
Which solution should a data architect use to comply with the DR policy?
Answer: B
Explanation:
The best solution to comply with the DR policy is to leverage a 3rd party tool that extract Salesforce data/metadata and stores the information in an external protected system. This solution can help create a backup of Salesforce data and metadata in case of a disaster or data loss event. It can also help restore data from the backup system to Salesforce if needed. There are various 3rd party tools available in the AppExchange or online that offer data backup and recovery services for Salesforce67. Leverage Salesforce weekly exports and store data in flat files on a protected system is not a good solution because it does not include metadata backup and it does not allow granular or automated data recovery. Utilize an ETL tool to migrate data to an on-premise archive solution is not a good solution because it does not include metadata backup and it may require complex data transformations and synchronizations. Write a custom batch job to extract data changes nightly and store in an external protected system is not a good solution because it does not include metadata backup and it may have performance or reliability issues.
NEW QUESTION # 139
What 2 data management policies does the data classification feature allow customers to classify in salesforce? Choose 2 answers:
Answer: B,D
Explanation:
The data classification feature allows customers to classify their data in Salesforce based on two policies:
Data sensitivity level: This policy defines how sensitive the data is and what level of protection it requires. For example, high sensitivity data may require encryption or masking.
Compliance categorization policy: This policy defines how the data is regulated by various laws and standards. For example, GDPR or PCI DSS.
NEW QUESTION # 140
Developers at Universal Containers need to build a report for the business which displays Accounts opened in the past year grouped by industry. This report will also include information from contacts, opportunities, and orders. There are several million Accounts in the system. Which two options should be recommended to make this report perform well and satisfy the business need?
Answer: B,C
NEW QUESTION # 141
Universal Containers has a rollup summary field on account to calculate the number of contacts associated with an account. During the account load, Salesforce is throwing an "UNABLE _TO_LOCK_ROW" error.
Which solution should a data architect recommend to resolve the error?
Answer: A
Explanation:
According to the Salesforce documentation1, the "UNABLE _TO_LOCK_ROW" error occurs when a record is being updated or created, and another operation tries to access or update the same record at the same time. This can cause lock contention and timeout issues. To resolve the error, some of the recommended solutions are:
Perform a batch job in serial mode and reduce the batch size (option B). This means running the batch job one at a time and processing fewer records per batch. This can reduce the chances of concurrent updates and lock contention on the same records.
Use the FOR UPDATE keyword to lock records in Apex code or API calls. This means explicitly locking the records that are being accessed or updated by a transaction, and preventing other transactions from modifying them until the lock is released. This can avoid conflicts and errors between concurrent operations on the same records2.
Defer rollup summary field calculation during data migration (option A). This means disabling the automatic calculation of rollup summary fields on the parent object when child records are inserted or updated. This can improve performance and avoid locking issues on the parent records. However, this option is only available for custom objects, not standard objects3.
Performing a batch job in parallel mode and reducing the batch size (option C) is not a good solution, as it can still cause lock contention and errors if multiple batches try to access or update the same records at the same time. Leveraging Data Loader's platform API to load data (option D) is also not a good solution, as it can still encounter locking issues if other operations are modifying the same records at the same time.
NEW QUESTION # 142
Universal Containers is integrating a new Opportunity engagement system with Salesforce. According to their Master Data Management strategy, Salesforce is the system of record for Account, Contact, and Opportunity dat a. However, there does seem to be valuable Opportunity data in the new system that potentially conflicts with what is stored in Salesforce. What is the recommended course of action to appropriately integrate this new system?
Answer: B
Explanation:
The recommended course of action to appropriately integrate the new Opportunity engagement system with Salesforce is to bring the stakeholders together to discuss the appropriate data strategy moving forward. This is because there may be valuable data in both systems that need to be reconciled and harmonized, and the Master Data Management (MDM) strategy may need to be revised or updated to accommodate the new system. The other options are not recommended, as they may result in data loss, inconsistency, or duplication
NEW QUESTION # 143
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