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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Master Data Management | 5% | - Describe the methods for aligning data across systems - Describe the considerations for a Master Data Management strategy |
| Topic 2: Data Governance | 10% | - Describe the considerations for data classification - Describe the considerations for data quality - Describe the elements of a data governance framework |
| Topic 3: 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 4: Data Migration | 15% | - Describe the implications of data migration on data quality - Describe the considerations for data migration - Describe the tools and best practices for data migration |
| Topic 5: Salesforce Data Management | 25% | - Describe the considerations for data archival - Describe the considerations for data governance - Describe the considerations for data migration - Describe the implications of LDV on data management |
| Topic 6: Data Modeling/Database Design | 25% | - Explain the usage of external objects - Describe the options and considerations for Large Data Volumes (LDV) - Describe the implications of LDV on data modeling - Describe the considerations when designing a data model for Salesforce |
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NEW QUESTION # 48
Get Cloudy Consulting is migrating their legacy system's users and data to Salesforce. They will be creating 15,000 users, 1.5 million Account records, and 15 million Invoice records. The visibility of these records is controlled by a 50 owner and criteria-based sharing rules. Get Cloudy Consulting needs to minimize data loading time during this migration to a new organization.
Which two approaches will accomplish this goal? (Choose two.)
Answer: B,D
Explanation:
Creating the users, uploading all data, and then deploying the sharing rules will reduce the number of sharing recalculations that occur during the data load. Deferring sharing calculations until the data has finished uploading will also improve the performance by postponing the sharing rule evaluation. These are the recommended best practices for loading large data sets into Salesforce
NEW QUESTION # 49
An Architect needs to document the data architecture for a multi-system, enterprise Salesforce implementation. Which two key artifacts should the Architect use? (Choose two.)
Answer: B,D
Explanation:
Option B is correct because data model is a key artifact that an architect should use to document the data architecture for a multi-system, enterprise Salesforce implementation. Data model describes the structure and relationship of data entities within an organization. Option C is correct because integration specification is another key artifact that an architect should use to document the data architecture for a multi-system, enterprise Salesforce implementation. Integration specification defines the scope, requirements, design, testing, and deployment of integration solutions between Salesforce and other systems.
NEW QUESTION # 50
A manager at Cloud Kicks is importing Leads into Salesforce and needs to avoid creating duplicate records. Which two approaches should the manager take to achieve this goal? (Choose two.)
Answer: B,C
Explanation:
Acquiring an AppExchange Lead de-duplication application and implementing Salesforce Matching and Duplicate Rules are two approaches that the manager at Cloud Kicks should take to avoid creating duplicate records when importing Leads into Salesforce. An AppExchange Lead de-duplication application can provide additional features and functionality for finding and preventing duplicate Leads during import, such as fuzzy matching, custom rules, mass merge, etc. Salesforce Matching and Duplicate Rules can allow the manager to define how Salesforce identifies duplicate Leads based on various criteria and how users can handle them during import, such as blocking, allowing, or alerting them. The other options are not feasible or effective for avoiding duplicate records, as they would either not work during import, not provide de- duplication capabilities, or require additional customization.
NEW QUESTION # 51
A custom pricing engine for a Salesforce customer has to be decided by factors with the following hierarchy:
- State in which the customer is located
- City in which the customer is located if available
- Zip code in which the customer is located if available
- Changes to this information should have minimum code changes
What should a data architect recommend to maintain this information for the custom pricing engine that is to be built in Salesforce?
Answer: A
Explanation:
According to the Get Started with Custom Metadata Types unit on Trailhead, one of the use cases for custom metadata types is to define custom charges for an accounting app. The unit states that "Say that your org uses a standard accounting app. You can create a custom metadata type that defines custom charges, like duties and VAT rates. Then you can write some Apex code that calculates the total amount due for each invoice by using the metadata from your custom metadata type." Therefore, a similar approach can be used to maintain the pricing criteria for a custom pricing engine in Salesforce.
NEW QUESTION # 52
Universal Containers has provided a web order form for its customer and has noticed invalid data coming in on orders. What should be used to mitigate this problem?
Answer: A
Explanation:
Using validation rules to mitigate this problem is the best option. Validation rules can help you prevent invalid data from being entered in your web order form. You can use validation rules to check for data quality, format, range, or consistency. For example, you can use validation rules to ensure that the order quantity is positive, the product code is valid, or the shipping address is complete.
NEW QUESTION # 53
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