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In order to be eligible for the Salesforce Data-Architect Certification Exam, candidates must have a Salesforce Certified Application Architect or Salesforce Certified System Architect certification. Additionally, candidates must have at least two years of experience in data architecture and design. Data-Architect Exam is computer-based and can be taken at a testing center or online. Once a candidate passes the exam, they will receive the Salesforce Certified Data Architect certification, which is a valuable credential in the Salesforce ecosystem that can open up many career opportunities.
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Salesforce Data-Architect Certification Exam is designed to test your knowledge of data architecture, modeling, and management within the Salesforce platform. Salesforce Certified Data Architect certification is intended for professionals who design and implement complex data solutions, and who have a deep understanding of data governance, data security, and data quality best practices.
Salesforce Data-Architect Certification Exam is a rigorous and challenging exam that requires extensive preparation and knowledge of Salesforce data architecture. Successful candidates will have demonstrated their expertise in designing and implementing data solutions on the Salesforce platform. Salesforce Certified Data Architect certification is a valuable asset for individuals seeking career advancement in the field of Salesforce data architecture and management. It is also a key differentiator for organizations looking to hire Salesforce professionals with advanced skills in data management and architecture.
NEW QUESTION # 201
Northern Trail Outfitter has implemented Salesforce for its associates nationwide, Senior management is concerned that the executive dashboard is not reliable for their real-time decision-making. On analysis, the team the following issues with data entered in Salesforce.
Information in certain records is incomplete.
Incorrect entry in certain fields causes records to be excluded in report fitters.
Duplicate entries cause incorrect counts.
Which three steps should a data architect recommend to address the issues?
Answer: A,D,E
Explanation:
According to the Salesforce documentation3, data quality is the measure of how well the data in Salesforce meets the expectations and requirements of the users and stakeholders. Data quality can be affected by various factors, such as data entry errors, data duplication, data inconsistency, data incompleteness, data timeliness, etc. To address the issues with data quality that affect the reliability of executive dashboards, a data architect should recommend:
Building a sales data warehouse with purpose-built data marts for dashboards and senior management reporting (option B). This means creating a separate database or system that stores and organizes sales data from Salesforce and other sources for analytical purposes. A data warehouse can provide a single source of truth for sales data and enable faster and more accurate reporting and analysis. A data mart is a subset of a data warehouse that focuses on a specific subject or business area, such as sales performance, customer segmentation, product profitability, etc. A data mart can provide tailored and relevant data for different users or groups based on their needs and interests.
Exploring third-party data providers to enrich and augment information entered in Salesforce (option C).
This means using external services or tools that can validate, correct, update, and enhance the data that is entered or imported into Salesforce. This can help improve data quality and accuracy, and reduce data duplication and incompleteness.
Leveraging Salesforce features, such as validation rules, to avoid incomplete and incorrect records (option D). This means using features that allow defining rules and criteria to validate the data that is entered or updated by the users or integrations. This can help prevent invalid or incorrect data from being saved, and trigger actions or alerts to correct or improve the data.
Periodically exporting data to cleanse data and import them back into Salesforce for executive reports (option A) is not a good solution, as it can be time-consuming, error-prone, and inefficient. It may also cause data inconsistency and synchronization issues between Salesforce and other systems. Designing and implementing data-quality dashboard to monitor and act on records that are incomplete or incorrect (option E) is also not a good solution, as it can be complex, costly, and difficult to maintain. It may also not address the root causes of data quality issues or prevent them from occurring in the first place.
NEW QUESTION # 202
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: A
NEW QUESTION # 203
DreamHouse Realty has a data model as shown in the image. The Project object has a private sharing model, and it has Roll-Up summary fields to calculate the number of resources assigned to the project, total hours for the project, and the number of work items associated to the project.
There will be a large amount of time entry records to be loaded regularly from an external system into Salesforce.
What should the Architect consider in this situation?
Answer: B
Explanation:
According to the exam guide, one of the objectives is to "describe the use cases and considerations for deferring sharing calculations"1. This implies that option A is the correct way to load large amounts of data into Salesforce without affecting performance and data integrity. Deferring sharing calculations allows the data to be loaded first and then the sharing rules to be applied later2. Option B is not correct because workflows are not recommended for calculating summary values, as they can cause performance issues and data skew3. Option C is not correct because triggers are also not recommended for calculating summary values, as they can cause governor limit errors and data inconsistency. Option D is not correct because external IDs are used to link records from different systems, not to improve data loading performance.
NEW QUESTION # 204
Northern Trail Outfitters (NTO) plans to maintain contact preferences for customers and employees. NTO has implemented the following:
1. Customers are Person Accounts for their retail business.
2. Customers are represented as Contacts for their commercial business.
3. Employees are maintained as Users.
4. Prospects are maintained as Leads.
NTO needs to implement a standard communication preference management model for Person Accounts, Contacts, Users, and Leads.
Which option should the data architect recommend NTO to satisfy this requirement?
Answer: C
NEW QUESTION # 205
Universal Containers is creating a new B2C service offering for consumers to ship goods across continents. This is in addition to their well-established B2B offering. Their current Salesforce org uses the standard Account object to track B2B customers. They are expecting to have over 50,000,000 consumers over the next five years across their 50 business regions. B2C customers will be individuals. Household data is not required to be stored. What is the recommended data model for consumer account data to be stored in Salesforce?
Answer: C
Explanation:
The recommended data model for consumer account data to be stored in Salesforce is to use the Account object with Person Accounts and a new B2C page layout. Person Accounts are a special type of accounts that allow you to store information about individual consumers who are not associated with a business account2. Person Accounts have the following advantages3:
They allow you to use the same standard objects and features that you use for business accounts, such as contacts, opportunities, cases, etc.
They enable you to create different page layouts and record types for B2C and B2B customers, which allows you to customize the user interface and business logic for each segment.
They support large data volumes and can scale up to 50 million records or more, which meets the expected growth of consumers over the next five years.
NEW QUESTION # 206
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