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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: 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 |
| Topic 2: Data Governance | 10% | - Describe the considerations for data classification - Describe the elements of a data governance framework - Describe the considerations for data quality |
| Topic 3: Large Data Volumes | 20% | - Describe the implications of LDV on data modeling - Describe the considerations for Large Data Volumes (LDV) - Describe the features and best practices for LDV |
| Topic 4: Master Data Management | 5% | - Describe the methods for aligning data across systems - Describe the considerations for a Master Data Management strategy |
| Topic 5: Salesforce Data Management | 25% | - Describe the considerations for data governance - Describe the implications of LDV on data management - Describe the considerations for data archival - Describe the considerations for data migration |
| Topic 6: Data Modeling/Database Design | 25% | - Describe the considerations when designing a data model for Salesforce - Explain the usage of external objects - Describe the implications of LDV on data modeling - Describe the options and considerations for Large Data Volumes (LDV) |
>> Exam Plat-Arch-201 Reference <<
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NEW QUESTION # 160
What ensures referential integrity?
Answer: B
Explanation:
Relationships ensure valid connections between records.
NEW QUESTION # 161
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: D
Explanation:
The best object model to configure within SF for migrating individual customers (B2C) data from legacy systems is to leverage person account object in Salesforce. Person accounts are a special type of accounts that store information about individual people by combining certain account and contact fields into a single record. Person accounts are useful for B2C scenarios where there is no need to associate a company name with a contact. Person accounts also support standard Salesforce features and functionality, such as leads, campaigns, reports, dashboards, etc.
Leverage custom person account object in SF is not a good option because there is no such thing as a custom person account object. Leverage custom account and contact object in SF is not a good option because it would require creating and maintaining additional objects and fields that may not be necessary or compatible with standard Salesforce features. Leverage standard account and contact object in SF is not a good option because it would require filling in dummy values for the account name field, which is mandatory for standard accounts.
NEW QUESTION # 162
Which factor impacts query selectivity the most?
Answer: B
Explanation:
Selectivity depends on how many records match the filter.
NEW QUESTION # 163
A company wants to document the data architecture of a Salesforce organization. What are two valid metadata types that should be included? (Choose two.)
Answer: A,B
Explanation:
Option A is correct because RecordType is a valid metadata type that should be included in documenting the data architecture of a Salesforce organization. RecordType defines different business processes, picklist values, and page layouts for different users. Option C is correct because CustomField is another valid metadata type that should be included in documenting the data architecture of a Salesforce organization. CustomField defines custom attributes for standard or custom objects.
NEW QUESTION # 164
NTO (Northern Trail Outlets) has a complex Salesforce org which has been developed over past
5 years. Internal users are complaining abt multiple data issues, including incomplete and duplicate data in the org. NTO has decided to engage a data architect to analyze and define data quality standards. Which 3 key factors should a data architect consider while defining data quality standards? Choose 3 Answer
Answer: A,C,E
Explanation:
Defining data duplication standards and rules, measuring data timeliness and consistency, and measuring data completeness and accuracy are three key factors that a data architect should consider while defining data quality standards. Defining data duplication standards and rules can help prevent or reduce duplicate records in the org by specifying criteria and actions for identifying and merging duplicates. Measuring data timeliness and consistency can help ensure that the data is up-to-date, reliable, and synchronized across different sources. Measuring data completeness and accuracy can help ensure that the data is sufficient, relevant, and correct for the intended purposes.
NEW QUESTION # 165
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