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| Section | Weight | Objectives |
|---|---|---|
| Data Integration | 15% | - ETL tools and data migration strategies - API-based integration (REST, SOAP, Bulk API) - Handling locks and parallelism during migration - Real-time vs batch integration patterns - Sharing rules impact on data integration |
| Data Governance | 20% | - Compliance and regulatory considerations - Data quality standards and metrics - Data retention and archiving policies - Data stewardship roles and responsibilities |
| Master Data Management | 20% | - Identity resolution - Data duplication and matching rules - Data cleansing techniques |
| Data Modeling | 25% | - Large Data Volumes (LDV) design considerations - Normalization and denormalization strategies - Skinny tables for performance optimization - Big Objects and external objects - Indexing strategies |
| Data Architecture | 20% | - Archiving and data lifecycle management - Performance tuning and optimization - Governor limits and bulk processing - Architecture patterns and design principles |
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NEW QUESTION # 24
Northern Trail Outfitters (NTO) wants to capture a list of customers that have bought a particular product. The solution architect has recommended to create a custom object for product, and to create a lookup relationship between its customers and its products.
Products will be modeled as a custom object (NTO_ Product__ c) and customers are modeled as person accounts. Every NTO product may have millions of customers looking up a single product, resulting in a lookup skew.
What should a data architect suggest to mitigate Issues related to lookup skew?
Answer: A
Explanation:
creating multiple similar products and distributing the skew across those products can be a way to mitigate issues related to lookup skew. The article explains that lookup skew happens when a very large number of records are associated with a single record in the lookup object, and this can cause record locking and performance issues. The article suggests creating multiple copies of the same product record and assigning different child records to each copy, so that the number of child records per parent record is reduced.
NEW QUESTION # 25
A customer is facing locking issued when importing large data volumes of order records that are children in a master-detail relationship with the Account object. What is the recommended way to avoid locking issues during import?
Answer: C
NEW QUESTION # 26
Universal Containers has received complaints that customers are being called by multiple Sales Reps where the second Sales Rep that calls is unaware of the previous call by their coworker. What is a data quality problem that could cause this?
Answer: A
Explanation:
A data quality problem that could cause customers to be called by multiple Sales Reps is having duplicate Contact records in the system. Duplicate records can result from data entry errors, data imports, or integrations with other systems. Duplicate records can lead to confusion, inefficiency, and customer dissatisfaction
NEW QUESTION # 27
Based on government regulations, a Salesforce customer plans to implement the following in Salesforce for compliance:
Access to customer information based on record ownership
Ability for customers to request removal of their information from Salesforce Prevent users from accessing Salesforce from outside company network (virtual private network, or VPN) What should a data architect recommend to address these requirements?
Answer: D
Explanation:
IP restrictions can be used to prevent users from accessing Salesforce from outside the company network or VPN. According to this article, sharing settings can be used to control access to customer information based on record ownership. According to this article, custom Apex can be used to support customer requests for removal of their information from Salesforce.
NEW QUESTION # 28
Universal Containers (UC) manages Vehicle and Service History in Salesforce. Vehicle (Vehicle__ c) and Service History (Service-History__ c) are both custom objects related through a lookup relationship.
Every week a batch synchronization process updates the Vehicle and Service History records in Salesforce.
UC has two hours of migration window every week and is facing locking issues as part of the data migration process.
What should a data architect recommend to avoid locking issues without affecting performance of data migration?
Answer: A
Explanation:
According to the official Salesforce guide1, using Bulk API serial mode for data migration can help avoid locking issues by processing batches in a single thread. This mode ensures that batches are processed in the order they are received and that only one batch is processed at a time. This reduces the risk of lock contention and deadlocks, especially when updating parent and child records in a lookup relationship. Option B is the correct answer because it suggests using Bulk API serial mode for data migration. Option A is incorrect because using Bulk API parallel mode for data migration can cause locking issues by processing batches in multiple threads. This mode does not guarantee the order of batch processing and can result in concurrent updates to the same records, which can lead to lock contention and deadlocks. Option C is incorrect because inserting the order in another custom object and using Batch Apex to move the records to Service_Order__c object adds unnecessary complexity and overhead to the data migration process. Option D is incorrect because changing the lookup configuration to "Clear the value of this field" when lookup record is deleted does not address the locking issues caused by data migration, but rather by record deletion.
NEW QUESTION # 29
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