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| Section | Weight | Objectives |
|---|---|---|
| Data Modeling | 25% | - Normalization and denormalization strategies - Indexing strategies - Big Objects and external objects - Large Data Volumes (LDV) design considerations - Skinny tables for performance optimization |
| Master Data Management | 20% | - Data cleansing techniques - Identity resolution - Data duplication and matching rules |
| Data Governance | 20% | - Data retention and archiving policies - Data stewardship roles and responsibilities - Data quality standards and metrics - Compliance and regulatory considerations |
| Data Integration | 15% | - ETL tools and data migration strategies - API-based integration (REST, SOAP, Bulk API) - Handling locks and parallelism during migration - Sharing rules impact on data integration - Real-time vs batch integration patterns |
| Data Architecture | 20% | - Performance tuning and optimization - Archiving and data lifecycle management - Architecture patterns and design principles - Governor limits and bulk processing |
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NEW QUESTION # 254
Universal Containers wants to implement a data -quality process to monitor the data that users are manually entering into the system through the Salesforce UI. Which approach should the architect recommend?
Answer: A
NEW QUESTION # 255
Universal Containers (UC) has built a custom application on Salesforce to help track shipments around the world. A majority of the shipping records are stored on premise in an external data source. UC needs shipment details to be exposed to the custom application, and the data needs to be accessible in real time. The external data source is not OData enabled, and UC does not own a middleware tool.
Which Salesforce Connect procedure should a data architect use to ensure UC's requirements are met?
Answer: D
NEW QUESTION # 256
Universal Containers (UC) has a Salesforce org with multiple automated processes defined for group membership processing, UC also has multiple admins on staff that perform manual adjustments to the role hierarchy. The automated tasks and manual tasks overlap daily, and UC is experiencing "lock errors" consistently.
What should a data architect recommend to mitigate these errors?
Answer: C
Explanation:
Enabling granular locking (option A) is the best recommendation to mitigate these errors, as it allows finer control over how records are locked during automated or manual processes, and reduces the chances of lock contention or deadlock. Removing SOQL statements from Apex Loops (option B) is a good practice for improving performance and avoiding governor limits, but it does not directly address the lock errors issue.
Enabling sharing recalculations (option C) is also not relevant for this issue, as it is used to update sharing rules and recalculate access for records. Asking Salesforce support for additional CPU power (option D) is also not a viable solution, as it does not solve the root cause of the lock errors.
NEW QUESTION # 257
UC is migrating individual customers (B2C) data from legacy systems to SF. There are millions of customers stored as accounts and contacts in legacy database.
Which object model should a data architect configure within SF ?
Answer: A
NEW QUESTION # 258
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 # 259
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