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| Section | Weight | Objectives |
|---|---|---|
| Data Governance | 20% | - Data quality standards and metrics - Data retention and archiving policies - Compliance and regulatory considerations - Data stewardship roles and responsibilities |
| Master Data Management | 20% | - Data cleansing techniques - Identity resolution - Data duplication and matching rules |
| Data Integration | 15% | - Sharing rules impact on data integration - ETL tools and data migration strategies - Real-time vs batch integration patterns - API-based integration (REST, SOAP, Bulk API) - Handling locks and parallelism during migration |
| Data Architecture | 20% | - Performance tuning and optimization - Architecture patterns and design principles - Archiving and data lifecycle management - Governor limits and bulk processing |
| Data Modeling | 25% | - Big Objects and external objects - Large Data Volumes (LDV) design considerations - Skinny tables for performance optimization - Indexing strategies - Normalization and denormalization strategies |
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58. Frage
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.)
Antwort: A,C
59. Frage
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?
Antwort: B
Begründung:
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.
60. Frage
What makes Skinny tables fast? Choose three answers.
Antwort: B,C,D
61. Frage
UC developers have created a new lightning component that uses an Apex controller using a SOQL query to populate a custom list view. Users are complaining that the component often fails to load and returns a time- out error.
What tool should a data architect use to identify why the query is taking too long?
Antwort: C
Begründung:
According to the Salesforce documentation 1 , the query plan tool is a tool that can be enabled and used in the developer console to analyze the performance of a SOQL query. The query plan tool shows the cost, cardinality, sObject type, and relative cost of each query plan that Salesforce considers for a query. The relative cost indicates how expensive a query plan is compared to the Force.com query optimizer threshold. A query plan with a relative cost above 1.0 is likely to cause a time-out error.
To identify why the query is taking too long, a data architect should use the query plan tool in the developer console (option B). This way, the data architect can see which query plan is chosen by Salesforce and how it affects the performance of the query. The data architect can also use the query plan tool to optimize the query by adding indexes, filters, or limits to reduce the cost and improve the efficiency of the query.
Using Splunk to query the system logs looking for transaction time and CPU usage (option A) is not a good solution, as it can be complex, costly, and difficult to integrate with Salesforce. It may also not provide enough information or insights to identify and optimize the query performance. Using Salesforce's query optimizer to analyze the query in the developer console (option C) is also not a good solution, as it is not a separate tool that can be used in the developer console. The query optimizer is a feature that runs automatically when a SOQL query is executed and chooses the best query plan based on various factors 2 .
Opening a ticket with Salesforce support to retrieve transaction logs to be analyzed for processing time (option D) is also not a good solution, as it can be time-consuming, dependent, and inefficient. It may also not provide enough information or insights to identify and optimize the query performance.
62. Frage
Universal Containers is setting up an external Business Intelligence (BI) system and wants to extract
1,000,000 Contact records. What should be recommended to avoid timeouts during the export process?
Antwort: D
Begründung:
According to the exam guide, one of the objectives is to " describe the use cases and considerations for using various tools and techniques for data migration (for example, Data Loader, Bulk API) " 1 . This implies that option B is the correct way to extract large volumes of data from Salesforce. The Bulk API is designed to handle large-scale data operations and avoid timeouts. Option A is not correct because the SOAP API is not optimized for large data sets and may encounter limits. Option C is not correct because GZIP compression does not prevent timeouts, but rather reduces the size of the data transferred. Option D is not correct because Batch Apex is used to process records asynchronously in Salesforce, not to export data to an external system.
63. Frage
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