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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Migration | 15% | - Migration execution and tools
|
| Topic 2: Master Data Management | 5% | - Golden record and system of truth
|
| Topic 3: Large Data Volumes and Performance | 20% | - Query and performance optimization
|
| Topic 4: Data Modeling and Database Design | 25% | - Data skew prevention
|
| Topic 5: Data Governance, Quality and Security | 15% | - Data quality management
|
| Topic 6: Data Integration | 20% | - Integration patterns and technologies
|
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NEW QUESTION # 255
Universal Containers (UC) is using Salesforce Sales & Service Cloud for B2C sales and customer service but they are experiencing a lot of duplicate customers in the system. Which are two recommended approaches for UC to avoid duplicate data and increase the level of data quality?
Answer: A,C
Explanation:
Using Duplicate Management and Data.com Clean are two recommended approaches for UC to avoid duplicate data and increase the level of data quality. Duplicate Management can prevent or alert users when they try to create or edit records that are duplicates of existing records.
Data.com Clean can compare Salesforce records with Data.com records and provide suggestions for updates or removals of duplicate records.
NEW QUESTION # 256
Universal Container require all customers to provide either a phone number of an email address when registering for an account. What should the data architect use to ensure this requirement is met?
Answer: A
Explanation:
Using a validation rule is the best way to ensure that all customers provide either a phone number or an email address when registering for an account, as it allows defining a formula that evaluates whether a record meets certain criteria. Using required fields may not work if both phone number and email address are required. Using an Apex class or a Process Builder may be more complex or cumbersome than using a validation rule.
NEW QUESTION # 257
Universal Containers (UC) is building a Service Cloud call center application and has a multisystem support solution. UC would like or ensure that all systems have access to the same customer information. What solution should a data architect recommend?
Answer: D
Explanation:
A master data management (MDM) strategy for customer data can help UC ensure that all systems have access to the same customer information, without loading or duplicating data in all systems. An MDM strategy can also help UC avoid data conflicts and inconsistencies that may arise from having multiple systems as owners of data.
NEW QUESTION # 258
A large retail company has recently chosen SF as its CRM solution. They have the following record counts:
- 2500000 accounts
- 25000000 contacts
When doing an initial performance test, the data architect noticed an extremely slow response for reports and list views.
What should a data architect do to solve the performance issue?
Answer: B
Explanation:
The correct answer is B, add custom indexes on frequently searched account and contact object fields. Custom indexes are a way to improve the performance of your queries and reports by creating indexes on specific fields that are often used in filters or joins. By adding custom indexes on frequently searched account and contact object fields, you can speed up the response time for reports and list views. Loading only the data that users are permitted to access, limiting data loading to the 2000 most recent records, or creating a skinny table are also possible solutions, but they are either not feasible, not scalable, or not supported by Salesforce.
NEW QUESTION # 259
Universal Containers (UC) has lead assignment rules to assign leads to owners. Leads not routed by assignment rules are assigned to a dummy user. Sales rep are complaining of high load times and issues with accessing leads assigned to the dummy user. What should a data architect recommend to solve these performance issues?
Answer: D
Explanation:
According to the official Salesforce guide, assigning leads to a single dummy user can cause performance issues and data skew, especially if the dummy user owns more than 10,000 records. Data skew occurs when a single user or a small number of users own a disproportionately large number of records, which can affect query performance and sharing calculations. Option B is the correct answer because it suggests creating multiple dummy users and assigning leads to them, which can distribute the load and reduce data skew.
NEW QUESTION # 260
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