Pass the Salesforce Application Architect Data-Architect Questions and answers with ExamsMirror

 Acquiring an AppExchange Lead de-duplication application and implementing Salesforce Matching and Duplicate Rules are two approaches that the manager at Cloud Kicks should take to avoid creating duplicate records when importing Leads into Salesforce. An AppExchange Lead de-duplication application can provide additional features and functionality for finding and preventing duplicate Leads during import, such as fuzzy matching, custom rules, mass merge, etc. Salesforce Matching and Duplicate Rules can allow the manager to define how Salesforce identifies duplicate Leads based on various criteria and how users can handle them during import, such as blocking, allowing, or alerting them. The other options are not feasible or effective for avoiding duplicate records, as they would either not work during import, not provide de-duplication capabilities, or require additional customization.

Defining data duplication standards and rules, measuring data timeliness and consistency, and measuring data completeness and accuracy are three key factors that a data architect should consider while defining data quality standards. Defining data duplication standards and rules can help prevent or reduce duplicate records in the org by specifying criteria and actions for identifying and merging duplicates. Measuring data timeliness and consistency can help ensure that the data is up-to-date, reliable, and synchronized across different sources. Measuring data completeness and accuracy can help ensure that the data is sufficient, relevant, and correct for the intended purposes.

 The best solution to make sure lead data has both profile and location information is to leverage external data providers to populate company profile and location data. This is because external data providers can enrich lead data with additional information from third-party sources, such as Dun & Bradstreet, ZoomInfo, or Clearbit. This can help improve lead quality, segmentation, and conversion. Salesforce supports integrating with external data providers using Data.com Clean or other AppExchange solutions2. Asking sales people to search for populating company profile and location data is inefficient and prone to errors. Running reports to identify records which do not have company profile and location data is useful, but does not solve the problem of how to populate the missing data. Exporting data out of Salesforce and sending to another team to populate company profile and location data is cumbersome and time-consuming.

Option B is the most appropriate approach for data archiving in this scenario1. By aggregating order amount data at a summary level and storing it in a custom object, you can reduce data storage and still provide visibility to the Sales Reps on how much money each customer generates year-over-year. Option A is not correct because storing data in a zip file does not make it available in Salesforce. Option C is not correct because exporting and deleting orders and order line items may lose important details that are needed for analysis or reporting. Option D is not correct because deleting orders and order line items without exporting them may cause data loss or inconsistency if the customer does not have order information in another system.

Indexing key fields used in report criteria can speed up the query execution and reduce the report run time. Indexes can be created by Salesforce automatically or manually by request. Creating one skinny table per report can also improve the reporting performance by storing frequently used fields in a separate table that does not include complex formulas or joins.

Leveraging Heroku Connect and Heroku Postgres, middleware tools, or Salesforce Connect and the cross-org adapter are all viable options to share data between Org A and Org B in near-real time3. Installing a 3rd party AppExchange tool may not provide bidirectional sync or may have additional costs. Developing an Apex class that pushes opportunity data between orgs daily via the Apex schedule may not meet the near-real time requirement.

According to the exam guide, one of the objectives is to "describe the use cases and considerations for using various tools and techniques for data migration (for example, Data Loader, Bulk API)"1. This implies that option B is the correct way to extract large volumes of data from Salesforce. The Bulk API is designed to handle large-scale data operations and avoid timeouts. Option A is not correct because the SOAP API is not optimized for large data sets and may encounter limits. Option C is not correct because GZIP compression does not prevent timeouts, but rather reduces the size of the data transferred. Option D is not correct because Batch Apex is used to process records asynchronously in Salesforce, not to export data to an external system.