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| Section | Objectives |
|---|---|
| Topic 1: Salesforce Data Model and Platform Capabilities | - Reporting and analytics considerations - Relationships and schema design - Standard and custom objects |
| Topic 2: Data Architecture and Design | - Handling large data volume and scalability considerations - Conceptual and logical data modeling - Data modeling best practices in Salesforce |
| Topic 3: Data Management | - Data governance principles - Master data management (MDM) concepts - Data quality management |
| Topic 4: Data Migration | - Data cleansing and transformation - Data migration strategies and planning |
| Topic 5: Data Integration | - API-based integration approaches - ETL vs ELT strategies - Integration patterns in Salesforce |
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NEW QUESTION # 90
A shipping and logistics company has created a large number of reports within Sales Cloud since Salesforce was introduced. Some of these reports analyze large amounts of data regarding the whereabouts of the company's containers, and they are starting to time out when users are trying to run the reports. What is a recommended approach to avoid these time-out issues?
Answer: D
Explanation:
Improving reporting performance by replacing the existing reports in Sales Cloud with new reports based on Analytics Cloud can avoid the time-out issues by leveraging the power and scalability of Analytics Cloud. Analytics Cloud can handle large volumes of data and provide faster and more interactive reports than Sales Cloud.
NEW QUESTION # 91
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: C
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 # 92
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: C,D
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 # 93
Universal Containers (UC) has 1,000 accounts and 50,000 opportunities. UC has an enterprise security requirement to export all sales data outside of Salesforce on a weekly basis. The security requirement also calls for exporting key operational data that includes events such as file downloads, logins, logouts, etc. Which two recommended approaches would address the above requirement?
Answer: A,D
Explanation:
Using Weekly Export to extract transactional data to on-premise systems and using Event Monitoring to extract event data to on-premise systems are two recommended approaches that would address the security requirement of UC. Weekly Export is a built-in feature that allows UC to download a zip file of their Salesforce data on a weekly basis. Event Monitoring is a tool that allows UC to access detailed information about various events that occur in their Salesforce org, such as logins, logouts, file downloads, etc.
NEW QUESTION # 94
Universal Containers is experiencing frequent and persistent group membership locking issues that severely restricts its ability to manage manual and a automated updates at the same time.
What should a data architect do in order to restore the issue?
Answer: C
Explanation:
Enabling granular locking allows concurrent sharing rule calculations and group membership updates to run without locking each other. This can help resolve the group membership locking issues that UC is experiencing.
NEW QUESTION # 95
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