Free Salesforce Data-Architect Practice Exam with Questions & Answers | Set: 6

The correct answer is B. To make changes efficiently, a data architect should enable Defer Sharing Calculation prior to making sharing rule changes. This will allow the administrator to make multiple changes to sharing rules without recalculating them after each change, which can take a long time and cause failures. The sharing rules can be recalculated later when there are fewer users online or during off-peak hours. Option A is incorrect because logging a case with salesforce to make sharing rule changes will not speed up the process or prevent failures. Option C is incorrect because deleting old sharing rules and building new sharing rules will not reduce the processing time or failure rate. Option D is incorrect because logging out all users and making changes to sharing rules will disrupt the business operations and may not be feasible.

Ensuring the lead data is preprocessed for quality before loading into Salesforce is the best way to maintain data quality2. Activating validation rules after the load or developing a custom Apex batch process may not catch all the errors or may require additional time and resources. Allowing validation rules to be activated during the load may cause failures or delays.

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.

The correct answer is C, create a geolocation custom field to maintain this requirement. A geolocation custom field is a compound field that can store both latitude and longitude information in a single field. It also supports geolocation functions and distance calculations. Creating formula fields or custom fields for latitude and longitude separately would be inefficient and redundant. Recommending app exchange packages would not be a direct solution to the requirement.

The best API for retrieving Salesforce org metadata programmatically is the Metadata API. The Metadata API provides access to the metadata that defines the structure and configuration of an org, such as custom objects, fields, workflows, security settings, etc. It also supports deploying, retrieving, creating, updating, and deleting metadata components. The Metadata API can be used with various tools, such as Ant, Workbench, or IDEs.

Exploring external data sources in Salesforce to build a 360 degree view of the customer (option A) is the best strategy to satisfy this requirement, as it allows customer service agents to view the activities from all four systems in real time without storing or replicating the data in Salesforce. Using a customer data mart to create the 360 degree view of the customer (option B) is not a good strategy, as it may introduce additional complexity and cost, and it does not leverage the native Salesforce features. Periodically uploading summary information in Salesforce to build a 360 degree view (option C) is also not a good strategy, as it may cause data latency and inconsistency, and it does not provide real-time information. Migrating customer activities from all four systems into Salesforce (option D) is also not a good strategy, as it may cause data redundancy and conflicts, and it does not scale well with large volumes of data.

 Data storage limits and API request limits are two important factors that affect the data integration and storage in Salesforce. Data storage limits determine how much data can be stored in Salesforce, and API request limits determine how many API calls can be made to Salesforce in a 24-hour period. Both of these limits depend on the edition and license type of the Salesforce org. Workflow rule limits and webservice callout limits are not directly related to data integration and storage, but rather to business logic and external services.

Shield platform encryption is the recommended solution for encrypting sensitive patient records stored in files, as it provides encryption at rest for files and attachments, as well as standard and custom fields. Classic encryption only supports text fields with a maximum length of 175 characters, and does not encrypt files. Third-party App Exchange apps may not provide the same level of security and compliance as shield platform encryption. Storing files outside of salesforce may introduce additional complexity and latency

single-select restricted picklist with defined choices can be a way to configure customer type. The article states that picklists are fields that allow users to select one or more predefined values from a list, and restricted picklists ensure that users can only select from the defined values. This can help to limit the choices for customer type and ensure data quality.

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.