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To become a Salesforce Certified Data Architect, candidates must have a solid understanding of the Salesforce platform, database architecture, data modeling, and data management. They must also have experience in designing and implementing data solutions that meet specific business requirements while ensuring data quality, security, and compliance. Data-Architect Exam covers topics such as data modeling, data integration, data quality, data security, and data governance, among others.
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Salesforce Data-Architect (Salesforce Certified Data Architect) Exam is a certification exam designed to test the knowledge and capabilities of professionals in the field of data architecture in the Salesforce ecosystem. It is a highly sought-after certification that validates the skills and experience of individuals in designing and implementing complex data solutions on the Salesforce platform.
Salesforce Data-Architect Certification Exam comprises scenarios that assess the candidate's ability to design, develop, and implement data solutions using Salesforce tools and technologies. Data-Architect Exam Tests the candidate's knowledge of data modeling, data integration, data migration, data governance, and data security. Candidates are expected to have a deep understanding of Salesforce's data architecture and its application to real-world business scenarios. They must also be proficient in using tools such as Salesforce Data Loader, Salesforce Connect, and Salesforce Shield.
NEW QUESTION # 43
Universal Containers is planning out their archiving and purging plans going forward for their custom objects Topic__c and Comment__c. Several options are being considered, including analytics snapshots, offsite storage, scheduled purges, etc. Which three questions should be considered when designing an appropriate archiving strategy?
Answer: A,B,C
Explanation:
The three questions that should be considered when designing an appropriate archiving strategy are: If reporting is necessary, can the information be aggregated into fewer, summary records? Will the data being archived need to be reported on or accessed in any way in the future? Are there any regulatory restrictions that will influence the archiving and purging plans? These questions are important because they help determine the scope, frequency, and method of archiving and purging data from Salesforce. For example, if reporting is necessary, then summary records or analytics snapshots can be used to store aggregated data and reduce the number of records that need to be archived1. If the data being archived needs to be accessed in the future, then offsite storage or external objects can be used to retain the data and make it available on demand2. If there are any regulatory restrictions, such as GDPR or HIPAA, then the archiving and purging plans need to comply with them and ensure data security and privacy
NEW QUESTION # 44
Universal Containers has defined a new Data Quality Plan for their Salesforce data and wants to know how they can enforce it throughout the organization. Which two approaches should an architect recommend to enforce this new plan?
Choose 2 answers
Answer: A,B
Explanation:
Scheduling a weekly dashboard displaying records that are missing information to be sent to managers for review and using Workflow, Validation Rules, and Force.com code (Apex) to enforce critical business processes are two approaches that an architect should recommend to enforce the new Data Quality Plan for UC's Salesforce data. Scheduling a weekly dashboard can provide a regular and visual way of monitoring the data quality and identifying any gaps or issues that need to be addressed by the managers or users. Using Workflow, Validation Rules, and Apex can provide various ways of enforcing data quality standards and business logic by automating actions, displaying error messages, or executing custom code when users create or edit records. The other options are not suitable or helpful for enforcing the Data Quality Plan, as they would either not provide real-time feedback, not prevent data quality issues, or not leverage the capabilities of Salesforce
NEW QUESTION # 45
Universal Containers (UC) has adopted Salesforce as its primary sales automated tool. UC has 100,00 customers with a growth rate of 10% a year, UC uses an on-premise web-based billing and invoice system that generates over 1 million invoices a year supporting a monthly billing cycle.
The UC sales team needs to be able to pull a customer record and view their account status, Invoice history, and opportunities without navigating outside of Salesforce.
What should a data architect use to provide the sales team with the required functionality?
Answer: A
Explanation:
To provide the sales team with the required functionality, a data architect should use a mashup page that will present the billing system records within Salesforce. A mashup page is a web page that combines data from multiple sources into a single integrated view. A mashup page can be created using Visualforce or Lightning Web Components, and can use Salesforce Connect or custom integrations to access external data from the on-premise web-based billing and invoice system. This will allow the sales team to pull a customer record and view their account status, invoice history, and opportunities without navigating outside of Salesforce. Option A is incorrect because creating a custom object and migrating the last 12 months of invoice data into Salesforce so it can be displayed on the account layout will consume a lot of storage space and may not reflect the latest data from the billing system. Option B is incorrect because writing an Apex callout and populating a related list to display on the account record will require additional development effort and may not be scalable or performant for large volumes of data. Option D is incorrect because creating a visual force tab with the billing system encapsulated within an iframe will not allow the sales team to view the billing system records within the customer record, but rather in a separate tab.
NEW QUESTION # 46
Universal Containers (UC) wants to ensure their data on 100,000 Accounts pertaining mostly to US-based companies is enriched and cleansed on an ongoing basis. UC is looking for a solution that allows easy monitoring of key data quality metrics. What should be the recommended solution to meet this requirement?
Answer: B
Explanation:
Using a declarative approach by installing and configuring Data.com Clean to monitor Account data quality can help UC meet their requirement. Data.com Clean can enrich and cleanse data on an ongoing basis by comparing Salesforce records with Data.com records and providing suggestions for updates. Data.com Clean can also provide dashboards and reports to monitor key data quality metrics such as match rate, field fill rate, and record completeness
NEW QUESTION # 47
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?
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 # 48
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