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| Exam Code: | Data-Architect |
| Exam Name: | Salesforce Certified Data Architect |
| Certification Provider: | Salesforce |
| Free Question Number: | 77 |
| Version: | v2023-03-15 |
| Rating: | |
| # of views: | 3212 |
| # of Questions views: | 91117 |
| Go To Data-Architect Questions | |
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No.# A is the answer
No.# D is correct
No.# A & C
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No.# its C & D
No.# A. Create a report combining data from the Account standard object and the Invoices external object.
Salesforce allows for the creation of reports that include data from both standard objects and external objects, assuming the external data is accessible via Salesforce Connect. This approach enables users to view integrated data from Accounts and Invoices within a single Salesforce report, providing a unified view of customer and financial data. This is a straightforward solution that leverages Salesforce's reporting capabilities to meet the requirement without the need for custom development or external reporting tools.
C. Create a Visualforce page combining Salesforce Account data and Invoice external object data.
If the reporting requirements are complex and cannot be fully addressed by standard Salesforce reporting capabilities, especially when combining data from standard and external objects, a custom Visualforce page can be developed. This approach offers greater flexibility in how data is displayed and allows for the incorporation of complex logic or custom user interfaces that go beyond the capabilities of standard reports. Visualforce pages can query both Salesforce data and external object data, enabling the creation of highly customized reports that meet specific business needs....
No.# A. Change Data Capture (CDC)
Change Data Capture is a feature that allows you to receive notifications about changes to Salesforce data (create, update, delete, undelete) in real-time. While CDC is powerful for tracking changes within a single Salesforce org, it's not specifically designed for sharing records between multiple Salesforce orgs.
No.# D. Integrate legacy CRM to Salesforce and keep data in synch till new functionality is in place.
This recommendation is based on the following considerations:
Data Synchronization: Integrating the legacy CRM with Salesforce ensures that data remains synchronized between the two systems during the transition period. This is crucial for maintaining operational continuity and ensuring that users have access to the most current and accurate information, regardless of which system they are using.
Seamless Transition: By keeping the legacy CRM and Salesforce in sync, UC can gradually transition processes and data to Salesforce without disrupting ongoing operations. This phased approach allows for testing and validation of Salesforce functionality while still relying on the legacy CRM where necessary.
Comprehensive Integration: Additionally, integrating Salesforce with SAP and ensuring that SAP is also integrated with the legacy CRM (as necessary) ensures that all critical business systems are connected. This holistic integration strategy supports a unified view of data across the organization's IT landscape, facilitating more informed decision-making and streamlined business processes....
No.# D. Maintain required pricing criteria in custom metadata types.
Custom Metadata Types in Salesforce are designed for storing and managing reusable sets of data that can be accessed across your org. This solution offers several key advantages for implementing a custom pricing engine with the described requirements:
Flexibility and Scalability: Custom Metadata Types allow you to create records that store the pricing criteria based on state, city, and zip code. Because these are metadata, they can be deployed across environments and referenced in code, making it easy to update pricing criteria without direct code changes.
Easy to Maintain and Update: Changes to pricing criteria can be made by updating the custom metadata records without needing to modify the code that references these records. This significantly reduces the maintenance overhead and allows for quick adjustments to pricing strategies as business needs evolve.
Integration with Custom Code: Custom Metadata Types can be directly accessed via Apex, Salesforce’s programming language, allowing the custom pricing engine to dynamically retrieve and apply the correct pricing criteria based on the customer’s location. This ensures that the engine can evaluate the hierarchy of location information to decide on pricing efficiently.
Deployment and Version Control: Unlike custom objects or configuration data, custom metadata types and their records can be included in package deployments and version control systems. This makes it easier to manage changes and ensure consistency across different Salesforce environments....
No.# D. Set up a staging database, and define external IDs to merge, clean duplicate data, and load into Salesforce.
This approach involves setting up an intermediary staging area (database) where data from both legacy systems can be consolidated. In this staging database, the data can be reviewed, cleaned, and deduplicated effectively before being loaded into Salesforce. External IDs can be used during this process to help with the identification of unique records and to assist in the deduplication process. This ensures that when the data is finally migrated to Salesforce, it is of high quality, free of duplicates, and structured correctly for Salesforce's data model.
No.# A. Keep searches specific and avoid wildcards where possible.
Specific searches yield more relevant results and perform better. While wildcards (*) can be useful for broad matching, they can also significantly increase the search scope, potentially slowing down the search operation and returning too many results. Starting a search with a wildcard, in particular, can be very inefficient.
C. Use searches against single Objects for greater speed and accuracy.
Searching against a single object, rather than multiple objects, can improve both the speed and accuracy of the search results. Narrowing down the search to a specific object limits the amount of data that SOSL needs to scan, resulting in faster and more relevant search outcomes.
No.# A. Load the contacts directly to Marketing Cloud and have a reconciliation process to track prospects that are converted to customers.
This recommendation is based on the following considerations:
By loading prospects directly into Marketing Cloud, UC can bypass the storage-intensive process of keeping all prospect data in the Sales Cloud. Marketing Cloud is designed to handle large volumes of marketing contacts and can manage these records efficiently for marketing campaigns.
Implementing a reconciliation process allows UC to identify which prospects have engaged or converted into customers. These records can then be selectively synced or created as Leads or Contacts in Sales Cloud, significantly reducing the volume of records that need to be stored in Sales Cloud.
This approach streamlines the marketing process, focusing storage and data management efforts in Sales Cloud on qualified leads and customers, thus optimizing storage usage and costs.
No.# A. Review projected data storage needs.
Understanding and planning for the additional data storage needs is crucial when implementing field-level audit and recovery mechanisms. Field history tracking, for example, consumes storage space, and the amount of data generated can be significant, especially for an organization concerned with daily data corruption. Planning for these storage needs ensures that the audit system remains viable and functional over time without exceeding Salesforce data storage limits.
No.# A. Ask support to create a skinny table for Application with the necessary reporting fields.
Skinny tables in Salesforce are used to improve the performance of read-only operations on large data volumes. They contain frequently used fields and are kept in sync with their source tables. By having a skinny table that includes the necessary fields for reporting, UC can experience faster report generation and query execution.
This approach is particularly effective for reports that use filters and need to process large volumes of data.
B. Add custom indexes to the Date fields used for filtering the report.
Custom indexing a field that is frequently used in report filters can significantly improve the performance of those reports. In UC's case, adding custom indexes to the Date fields used for filtering will help optimize the query execution plan and reduce the time taken to retrieve the relevant data.
Salesforce automatically indexes some standard fields like Id, Name, etc., but for custom fields or specific use cases, requesting custom indexing is a beneficial approach....
No.# D. Leverage a mashup to display historical records in Salesforce.
This recommendation is based on the following considerations:
A mashup integrates external data into the Salesforce UI, allowing users to view and interact with data stored in external systems without the need to migrate it into Salesforce. This approach is ideal for UC's requirement to access historical data from the legacy system within Salesforce.
Mashups can be implemented using techniques like iframes or Salesforce Canvas, enabling Salesforce to display data from the legacy system in real-time. This provides a seamless user experience, allowing users to access historical data as if it were part of Salesforce.
This solution avoids the need for large-scale data migration and the associated storage costs and complexities while still providing access to the necessary historical records.
The other options:
The test was not easy as there are a lot of Salesforce material to cover.
No.# Error on question 56 when trying to go to 57 - bad url
Skip to q 58 using this link https://www.freecram.net/question/Salesforce.Data-Architect.v2023-03-15.q77/during-the-implementation-of-salesforce-a-customer-has-the-following-requirements-for-sales-orders
No.# Correct is A C E
A. They support up to a max of 100 of columns
C. They avoid resource intensive joins
E. They do not include soft-deleted records
https://developer.salesforce.com/docs/atlas.en-us.salesforce_large_data_volumes_bp.meta/salesforce_large_data_volumes_bp/ldv_deployments_infrastructure_skinny_tables.htm