Data-Architect Latest Exam Question, Vce Data-Architect Exam

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To become a Salesforce Certified Data Architect, you must first meet the prerequisites for the certification. This includes earning the Salesforce Certified Application Architect and Salesforce Certified System Architect certifications, as well as completing the Data Architecture and Management Designer certification. Once these prerequisites are met, you can then take the Salesforce Data-Architect certification exam.

Salesforce Data-Architect certification is highly valued in the industry, as it demonstrates the candidate's ability to design and manage complex data solutions on the Salesforce platform. It is a highly specialized certification that requires a deep understanding of Salesforce data architecture principles and best practices, as well as hands-on experience in implementing data solutions in real-world scenarios.

To qualify for this certification exam, candidates must have a minimum of 3-5 years of experience in data architecture, as well as a deep understanding of the Salesforce platform and its data model. Data-Architect Exam itself consists of multiple-choice questions and scenario-based questions, which are designed to test the candidate's knowledge and ability to apply best practices in data architecture to real-world scenarios. Once certified, professionals will have the skills and knowledge necessary to design and implement complex data solutions that can help organizations better understand their customers, improve their sales and marketing efforts, and drive business growth. Overall, the Salesforce Data-Architect Certification is a valuable credential for any data professional looking to advance their career in the Salesforce ecosystem.

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Salesforce Certified Data Architect Sample Questions (Q251-Q256):

NEW QUESTION # 251
Northern Trail Outfitters <NTO> is streaming IoT data from connected devices to a cloud database. Every 24 hours. 100,000 records are generated.
NIO employees will need to see these lol records within Salesforce and generate weekly reports on it. Developers may also need to write programmatic logic to aggregate the records and incorporate them into workflows.
Which data pattern will allow a data architect to satisfy these requirements, while also keeping limits in mind?

A. Unidirectional integration
B. Persistence
C. Bidirectional integration
D. Virtualization

Answer: B

Explanation:
Persistence is the data pattern that will allow a data architect to satisfy the requirements, while also keeping limits in mind. Persistence means storing data from external sources in Salesforce objects, either standard or custom. This allows you to access the data within Salesforce and use it for reporting, analytics, workflows, and other features. Persistence also helps you avoid hitting API limits or performance issues when accessing large volumes of data from external systems. You can use various tools such as Data Loader, Bulk API, or Platform Events to persist IoT data from connected devices to a cloud database in Salesforce.

NEW QUESTION # 252
NTO has been using salesforce for sales and service for 10 years. For the past 2 years, the marketing group has noticed a raise from 0 to 35 % in returned mail when sending mail using the contact information stored in salesforce.
Which solution should the data architect use to reduce the amount of returned mails?

A. Delete contacts when the mail is returned to save postal cost to NTO.
B. Have the sales team to call all existing customers and ask to verify the contact details.
C. Use a 3rd-party data source to update contact information in salesforce.
D. Email all customer and asked them to verify their information and to call NTO if their address is incorrect.

Answer: C

NEW QUESTION # 253
Which two aspects of data does an Enterprise data governance program aim to improve?

A. Data integrity
B. Data usability
C. Data distribution
D. Data modeling

Answer: A,B

NEW QUESTION # 254
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 backup and archive solution that extracts and restores data across orgs.
C. Develop custom APIs to poll the spoke for change data and push into the org.
D. A middleware solution that extracts and distributes data across both the hub and spokes.

Answer: D

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 # 255
Universal Containers has multiple systems all containing and maintaining customer dat a. Although point-to-point integrations are in place, customers are complaining about consistency in the data.
What solution should the data architect recommend?

A. Improve existing point-to-point integrations
B. An MDM solution as the customer master, with centralized integrations to ensure consistency across all systems.
C. Perform a onetime synchronization to level set the built up inconsistencies
D. Data cleanse each system

Answer: B

Explanation:
Master data management (MDM) is a solution that helps organizations manage their master data across multiple systems and ensure consistency and quality. An MDM solution can act as the customer master, with centralized integrations to other systems, to avoid data duplication and inconsistency.

NEW QUESTION # 256
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Data-Architect Latest Exam Question, Vce Data-Architect Exam

Vce Data-Architect Exam - 100% Data-Architect Correct Answers

Salesforce Certified Data Architect Sample Questions (Q251-Q256):

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