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Salesforce Certified Data Architect exam is a challenging and comprehensive test that evaluates a candidate's expertise in various areas of data architecture. Data-Architect Exam covers topics such as data modeling, data integration, data governance, data security, data migration, and data quality. Data-Architect exam consists of 60 multiple-choice questions and has a duration of 120 minutes. A passing score of 70% or higher is required to obtain the certification.

Salesforce Certified Data Architect certification exam is one of the most prestigious certifications in the Salesforce ecosystem. It is intended for professionals who have experience in designing and developing data solutions using Salesforce. Salesforce Certified Data Architect certification exam covers a wide range of topics, including data modeling, data architecture, data integration, data storage, and data governance.

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Salesforce Certified Data Architect Sample Questions (Q225-Q230):

NEW QUESTION # 225
Universal Container has implemented Sales Cloud to manage patient and related health records. During a recent security audit of the system, it was discovered that same standard and custom fields need to encrypted.
Which solution should a data architect recommend to encrypt existing fields?

A. Use Apex Crypto Class encrypt customer and standard fields.
B. Implement shield platform encryption to encrypt and standard fields
C. Expert data out of Salesforce and encrypt custom and standard fields.
D. Implement classic encryption to encrypt custom and standard fields.

Answer: B

Explanation:
The correct answer is C, implement shield platform encryption to encrypt standard and custom fields. Shield platform encryption is a feature that allows you to encrypt sensitive data at rest in Salesforce without affecting its functionality. You can encrypt both standard and custom fields using shield platform encryption. Using Apex Crypto Class, implementing classic encryption, or exporting data out of Salesforce are not recommended solutions, as they will either limit your functionality, require custom code, or compromise your data security.

NEW QUESTION # 226
UC has a legacy client server app that as a relational data base that needs to be migrated to salesforce.
What are the 3 key actions that should be done when data modeling in salesforce?
Choose 3 answers:

A. Work with legacy application owner to analysis legacy data model.
B. Implement legacy data model within salesforce using custom fields.
C. Map legacy data to salesforce objects.
D. Identify data elements to be persisted in salesforce.
E. Map legacy data to salesforce custom objects.

Answer: B,C,D

NEW QUESTION # 227
UC has millions of Cases and are running out of storage. Some user groups need to have access to historical cases for up to 7 years.
Which 2 solutions should a data architect recommend in order to minimize performance and storage issues?
Choose 2 answers:

A. Create a custom object to store case history and run reports on it.
B. Leverage on premise data archival and build integration to view archived data.
C. Leverage big object to archive case data and lightning components to show archived data.
D. Export data out of salesforce and store in Flat files on external system.

Answer: B,C

Explanation:
The correct answer is C and D. To minimize performance and storage issues, a data architect should recommend leveraging on premise data archival and building integration to view archived data, and leveraging big object to archive case data and lightning components to show archived data. These solutions will allow some user groups to access historical cases for up to 7 years without consuming too much storage space or affecting the performance of queries and reports. Option A is incorrect because exporting data out of salesforce and storing it in flat files on external system will make it difficult to access and query the data. Option B is incorrect because creating a custom object to store case history and run reports on it will still consume a lot of storage space and impact the performance of queries and reports.

NEW QUESTION # 228
North Trail Outfitters (NTO) operates a majority of its business from a central Salesforce org, NTO also owns several secondary orgs that the service, finance, and marketing teams work out of, At the moment, there is no integration between central and secondary orgs, leading to data-visibility issues.
Moving forward, NTO has identified that a hub-and-spoke model is the proper architect to manage its data, where the central org is the hub and the secondary orgs are the spokes.
Which tool should a data architect use to orchestrate data between the hub org and spoke orgs?

A. Develop custom APIs to poll the hub org for change data and push into the spoke orgs.
B. A middleware solution that extracts and distributes data across both the hub and spokes.
C. A backup and archive solution that extracts and restores data across orgs.
D. Develop custom APIs to poll the spoke for change data and push into the org.

Answer: B

Explanation:
According to the Salesforce documentation, a hub-and-spoke model is an integration architecture pattern that allows connecting multiple Salesforce orgs using a central org (hub) and one or more secondary orgs (spokes). The hub org acts as the master data source and orchestrates the data flow between the spoke orgs. The spoke orgs act as the consumers or producers of the data and communicate with the hub org.
To orchestrate data between the hub org and spoke orgs, a data architect should use:
A middleware solution that extracts and distributes data across both the hub and spokes (option A). This means using an external service or tool that can connect to multiple Salesforce orgs using APIs or connectors, and perform data extraction, transformation, and distribution operations between the hub and spoke orgs. This can provide a scalable, flexible, and reliable way to orchestrate data across multiple orgs.
Developing custom APIs to poll the hub org for change data and push into the spoke orgs (option B) is not a good solution, as it can be complex, costly, and difficult to maintain. It may also not be able to handle large volumes of data or complex transformations efficiently. Developing custom APIs to poll the spoke orgs for change data and push into the hub org (option C) is also not a good solution, as it can have the same drawbacks as option B. It may also not be able to handle conflicts or errors effectively. Using a backup and archive solution that extracts and restores data across orgs (option D) is also not a good solution, as it can incur additional costs and dependencies. It may also not be able to handle real-time or near-real-time data orchestration requirements.

NEW QUESTION # 229
Salesforce is being deployed in Ursa Major Solar's disparate, multi-system ERP environment. Ursa major Solar wants to maintain data synchronization between systems.
Which two techniques should be used to achieve this goal? (Choose two.)

A. Utilize an MDM strategy to outline a single source of truth.
B. Build synchronization reports and dashboards.
C. Utilize workbench to update files within systems.
D. Integrate Salesforce with the ERP environment.

Answer: A,D

Explanation:
Option A is correct because integrating Salesforce with the ERP environment is a technique to maintain data synchronization between systems1. Option C is correct because utilizing an MDM strategy to outline a single source of truth is another technique to ensure data quality and consistency across systems2. Option B is not correct because utilizing workbench to update files within systems is not a technique to maintain data synchronization, but a tool to perform data manipulation tasks3. Option D is not correct because building synchronization reports and dashboards is not a technique to maintain data synchronization, but a way to monitor and analyze data4.

NEW QUESTION # 230
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