NEW SOFT DATA-ARCHITECT SIMULATIONS - RELIABLE DATA-ARCHITECT TEST TIPS

New Soft Data-Architect Simulations - Reliable Data-Architect Test Tips

New Soft Data-Architect Simulations - Reliable Data-Architect Test Tips

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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.

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Salesforce Certified Data Architect Sample Questions (Q229-Q234):

NEW QUESTION # 229
Universal Containers (UC) manages Vehicle and Service History in Salesforce. Vehicle (Vehicle__ c) and Service History (Service-History__ c) are both custom objects related through a lookup relationship.
Every week a batch synchronization process updates the Vehicle and Service History records in Salesforce. UC has two hours of migration window every week and is facing locking issues as part of the data migration process.
What should a data architect recommend to avoid locking issues without affecting performance of data migration?

  • A. Change the lookup configuration to "Clear the value of this field" when lookup record is deleted.
  • B. Use Bulk API serial mode for data migration
  • C. Insert the order in another custom object and use Batch Apex to move the records to Service_ Order__ c object.
  • D. Use Bulk API parallel mode for data migration

Answer: B

Explanation:
According to the official Salesforce guide1, using Bulk API serial mode for data migration can help avoid locking issues by processing batches in a single thread. This mode ensures that batches are processed in the order they are received and that only one batch is processed at a time. This reduces the risk of lock contention and deadlocks, especially when updating parent and child records in a lookup relationship. Option B is the correct answer because it suggests using Bulk API serial mode for data migration. Option A is incorrect because using Bulk API parallel mode for data migration can cause locking issues by processing batches in multiple threads. This mode does not guarantee the order of batch processing and can result in concurrent updates to the same records, which can lead to lock contention and deadlocks. Option C is incorrect because inserting the order in another custom object and using Batch Apex to move the records to Service_Order__c object adds unnecessary complexity and overhead to the data migration process. Option D is incorrect because changing the lookup configuration to "Clear the value of this field" when lookup record is deleted does not address the locking issues caused by data migration, but rather by record deletion.


NEW QUESTION # 230
UC developers have created a new lightning component that uses an Apex controller using a SOQL query to populate a custom list view. Users are complaining that the component often fails to load and returns a time-out error.
What tool should a data architect use to identify why the query is taking too long?

  • A. Open a ticket with salesforce support to retrieve transaction logs to e analyzed for processing time.
  • B. Use salesforce's query optimizer to analyze the query in the developer console.
  • C. Enable and use the query plan tool in the developer console.
  • D. Use Splunk to query the system logs looking for transaction time and CPU usage.

Answer: C

Explanation:
According to the Salesforce documentation1, the query plan tool is a tool that can be enabled and used in the developer console to analyze the performance of a SOQL query. The query plan tool shows the cost, cardinality, sObject type, and relative cost of each query plan that Salesforce considers for a query. The relative cost indicates how expensive a query plan is compared to the Force.com query optimizer threshold. A query plan with a relative cost above 1.0 is likely to cause a time-out error.
To identify why the query is taking too long, a data architect should use the query plan tool in the developer console (option B). This way, the data architect can see which query plan is chosen by Salesforce and how it affects the performance of the query. The data architect can also use the query plan tool to optimize the query by adding indexes, filters, or limits to reduce the cost and improve the efficiency of the query.
Using Splunk to query the system logs looking for transaction time and CPU usage (option A) is not a good solution, as it can be complex, costly, and difficult to integrate with Salesforce. It may also not provide enough information or insights to identify and optimize the query performance. Using Salesforce's query optimizer to analyze the query in the developer console (option C) is also not a good solution, as it is not a separate tool that can be used in the developer console. The query optimizer is a feature that runs automatically when a SOQL query is executed and chooses the best query plan based on various factors2. Opening a ticket with Salesforce support to retrieve transaction logs to be analyzed for processing time (option D) is also not a good solution, as it can be time-consuming, dependent, and inefficient. It may also not provide enough information or insights to identify and optimize the query performance.


NEW QUESTION # 231
Universal Containers (UC) manages Vehicle and Service History in Salesforce. Vehicle (Vehicle__ c) and Service History (Service-History__ c) are both custom objects related through a lookup relationship.
Every week a batch synchronization process updates the Vehicle and Service History records in Salesforce.
UC has two hours of migration window every week and is facing locking issues as part of the data migration process.
What should a data architect recommend to avoid locking issues without affecting performance of data migration?

  • A. Change the lookup configuration to "Clear the value of this field" when lookup record is deleted.
  • B. Use Bulk API serial mode for data migration
  • C. Insert the order in another custom object and use Batch Apex to move the records to Service_ Order__ c object.
  • D. Use Bulk API parallel mode for data migration

Answer: B

Explanation:
According to the official Salesforce guide1, using Bulk API serial mode for data migration can help avoid locking issues by processing batches in a single thread. This mode ensures that batches are processed in the order they are received and that only one batch is processed at a time. This reduces the risk of lock contention and deadlocks, especially when updating parent and child records in a lookup relationship. Option B is the correct answer because it suggests using Bulk API serial mode for data migration. Option A is incorrect because using Bulk API parallel mode for data migration can cause locking issues by processing batches in multiple threads. This mode does not guarantee the order of batch processing and can result in concurrent updates to the same records, which can lead to lock contention and deadlocks. Option C is incorrect because inserting the order in another custom object and using Batch Apex to move the records to Service_Order__c object adds unnecessary complexity and overhead to the data migration process. Option D is incorrect because changing the lookup configuration to "Clear the value of this field" when lookup record is deleted does not address the locking issues caused by data migration, but rather by record deletion.


NEW QUESTION # 232
Get Cloudy Consulting needs to evaluate the completeness and consistency of contact information in Salesforce. Their sales reps often have incomplete information about their accounts and contacts. Additionally, they are not able to interpret the information in a consistent manner. Get Cloudy Consulting has identified certain ""key"" fields which are important to their sales reps.
What are two actions Get Cloudy Consulting can take to review their data for completeness and consistency? (Choose two.)

  • A. Run one report per key field, grouped by that field, to understand its data variability.
  • B. Run a report which shows the last time the key fields were updated.
  • C. Run a process that can fill in default values for blank fields.
  • D. Run a report that shows the percentage of blanks for the important fields.

Answer: B,D

Explanation:
Running a report that shows the last time the key fields were updated can help Get Cloudy Consulting identify stale or outdated data and prioritize data cleansing activities. Running a report that shows the percentage of blanks for the important fields can help Get Cloudy Consulting measure the completeness of their data and identify gaps or missing value


NEW QUESTION # 233
Universal Containers (CU) is in the process of implementing an enterprise data warehouse (EDW). UC needs to extract 100 million records from Salesforce for migration to the EDW.
What data extraction strategy should a data architect use for maximum performance?

  • A. Call the REST API in successive queries.
  • B. Use the Bulk API in parallel mode.
  • C. Utilize PK Chunking with the Bulk API.
  • D. Install a third-party AppExchange tool.

Answer: C

Explanation:
According to the Salesforce documentation2, extracting large amounts of data from Salesforce can be challenging and time-consuming, as it can encounter performance issues, API limits, timeouts, etc. To extract
100 million records from Salesforce for migration to an enterprise data warehouse (EDW), a data extraction strategy that can provide maximum performance is:
Utilize PK Chunking with the Bulk API (option C). This means using a feature that allows splitting a large query into smaller batches based on the record IDs (primary keys) of the queried object. This can improve performance and avoid timeouts by processing each batch asynchronously and in parallel using the Bulk API3.
Installing a third-party AppExchange tool (option A) is not a good solution, as it can incur additional costs and dependencies. It may also not be able to handle such a large volume of data efficiently. Calling the REST API in successive queries (option B) is also not a good solution, as it can encounter API limits and performance issues when querying such a large volume of data. Using the Bulk API in parallel mode (option D) is also not a good solution, as it can still cause timeouts and errors when querying such a large volume of data without chunking.


NEW QUESTION # 234
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