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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Governance | 10% | - Describe the considerations for data classification - Describe the considerations for data quality - Describe the elements of a data governance framework |
| Topic 2: Large Data Volumes | 20% | - Describe the features and best practices for LDV - Describe the considerations for Large Data Volumes (LDV) - Describe the implications of LDV on data modeling |
| Topic 3: Master Data Management | 5% | - Describe the considerations for a Master Data Management strategy - Describe the methods for aligning data across systems |
| Topic 4: Data Modeling/Database Design | 25% | - Describe the considerations when designing a data model for Salesforce - Explain the usage of external objects - Describe the options and considerations for Large Data Volumes (LDV) - Describe the implications of LDV on data modeling |
| Topic 5: 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 |
| Topic 6: Data Migration | 15% | - Describe the tools and best practices for data migration - Describe the considerations for data migration - Describe the implications of data migration on data quality |
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NEW QUESTION # 82
Universal Containers (UC) is going thought major reorganization of their sales team. This would require changes to a large a number of group members and sharing rules. UCs administrator is concerned about long processing time and failure during the process. What should a Data architect implement to make changes efficiently?
Answer: A
Explanation:
The correct answer is B. To make changes efficiently, a data architect should enable Defer Sharing Calculation prior to making sharing rule changes. This will allow the administrator to make multiple changes to sharing rules without recalculating them after each change, which can take a long time and cause failures. The sharing rules can be recalculated later when there are fewer users online or during off-peak hours.
NEW QUESTION # 83
Universal Containers (UC) is migrating from an on-premise homegrown customer relationship management (CRM) system. During analysis, UC users highlight a pain point that there are multiple versions of many customers. What should the data architect do for a successful migration to mitigate the pain point?
Answer: A
Explanation:
Storing the data in a staging database and de-duplicating identical records (option D) is the best solution for a successful migration to mitigate the pain point, as it allows the data architect to identify and merge duplicate customers before they are imported into Salesforce.
NEW QUESTION # 84
NTO need to extract 50 million records from a custom object everyday from its Salesforce org.
NTO is facing query timeout issues while extracting these records. What should a data architect recommend in order to get around the time out issue?
Answer: A
Explanation:
The best solution to extract 50 million records from a custom object everyday from Salesforce org without facing query timeout issues is to use an ETL tool for extraction of records. ETL stands for extract, transform, and load, and it refers to a process of moving data from one system to another. An ETL tool is a software application that can connect to various data sources, perform data transformations, and load data into a target destination. ETL tools can handle large volumes of data efficiently and reliably, and they often provide features such as scheduling, monitoring, error handling, and logging. Using a custom auto number and formula field and use that to chunk records while extracting data is a possible workaround, but it requires creating additional fields and writing complex queries. The REST API can extract data as it automatically chunks records by 200, but it has some limitations, such as a maximum of 50 million records per query job.
Asking SF support to increase the query timeout value is not feasible because query timeout values are not configurable
NEW QUESTION # 85
DreamHouse Realty has a Salesforce deployment that manages Sales, Support, and Marketing efforts in a multi-system ERP environment. The company recently reached the limits of native reports and dashboards and needs options for providing more analytical insights. What are two approaches an Architect should recommend? (Choose two.)
Answer: A,D
Explanation:
Einstein Analytics can provide more analytical insights than native reports and dashboards by allowing users to explore data from multiple sources, create interactive visualizations, and apply AI-powered features. AppExchange Apps can also provide more analytical insights by offering pre-built solutions or integrations with external tools that can enhance the reporting and analytics capabilities of Salesforce6.
NEW QUESTION # 86
Universal Containers (UC) wants to store product data in Salesforce, but the standard Product object does not support the more complex hierarchical structure which is currently being used in the product master system. How can UC modify the standard Product object model to support a hierarchical data structure in order to synchronize product data from the source system to Salesforce?
Answer: D
Explanation:
Creating a custom lookup field on the standard Product to reference the parent record in the hierarchy is the correct way to modify the standard Product object model to support a hierarchical data structure. This allows UC to create a self-relationship on the Product object and define parent-child relationships among products.
NEW QUESTION # 87
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