Data-Architect Salesforce Certified Data Architect (SU24) Questions and Answers

The recommended solution to address the requirements of Universal Containers (UC) is to roll-up discount request amount at the line-item-level and line-item-level summary discount at the opportunity level. This solution would allow UC to show all sums of discounts across line items at an opportunity level using standard roll-up summary fields. Since UC has a multi-level master-detail relationship for opportunities, a custom opportunity line item object, and a custom discount request object, they can use two levels of roll-up summary fields to aggregate the discount amounts from the child objects to the parent objects. For example, they can create a roll-up summary field on the custom line item object to sum up the discount request amounts from the custom discount request object. Then, they can create another roll-up summary field on the opportunity object to sum up the line-item-level summary discounts from the custom line item object.

To improve the dashboard performance, the data architect should use selective queries to reduce the amount of data being returned, de-normalize the data by reducing the number of joins, and reduce the amount of data queried by archiving unused opportunity records. These optionswill help optimize the query performance, reduce the query complexity, and free up storage space. Option C is incorrect because removing widgets from the dashboard to reduce the number of graphics loaded will not affect the dashboard performance significantly, and may reduce the usability and functionality of the dashboard. Option D is incorrect because running the dashboard for CEO and sending it via email will not improve the dashboard performance, but rather shift the burden to another user.

The correct answer is C, implement shield platform encryption to encrypt standard and custom fields. Shield platform encryption is a feature that allows you to encrypt sensitive data at rest in Salesforce without affecting its functionality. You can encrypt both standard and custom fields using shield platform encryption. Using Apex Crypto Class, implementing classic encryption, or exporting data out of Salesforce are not recommended solutions, as they will either limit your functionality, require custom code, or compromise your data security.

Making use of a third-party tool to help merge duplicate Contacts across Accounts and using Data.com to standardize Contact address information to help identify duplicates are two solutions that UC should implement to cleanse their data and have a single Contact across departments. A third-party tool, such as an app from the AppExchange, can provide advanced features and capabilities for findingand merging duplicate Contacts across different Accounts, based on various criteria and rules. Data.com can provide address verification and standardization services that can enhance the quality and consistency of Contact address information and make it easier to identify duplicates. The other options are not feasible or effective for cleansing the data, as they would either not work across different Accounts, not address the root cause of duplication, or not provide sufficient functionality for merging duplicates

According to the Salesforce documentation1, reporting performance can be affected by various factors, such as the volume and complexity of data, the design and configuration of reports and dashboards, the number and type of users accessing the reports, etc. To improve reporting performance, some of the recommended solutions are:

Move data off of the platform and run reporting outside Salesforce, and give access to reports (option C). This means using an external service or tool that can extract, transform, and load (ETL) data from Salesforce to another system or database, such as a data warehouse or a business intelligence platform. This can improve reporting performance by reducing the load and latency on Salesforce, and enabling faster and more flexible reporting and analysis on the external system. Users can access the reports from the external system using a link or an embedded component in Salesforce.

Contact Salesforce support to enable skinny table for cases (option B). This means requesting Salesforce to create a custom table that contains asubset of fields from the Case object that are frequently used or queried. A skinny table can improve reporting performance by avoiding joins between standard and custom fields, omitting soft-deleted records, and leveraging indexes on the fields2.

Create a custom object to store aggregate data and run reports (option A). This means creating a custom object that contains summary or calculated data from the Case object, such as counts, sums, averages, etc. A custom object can improve reporting performance by reducing the number ofrecords and fields that need to be queried and displayed.

Build reports using custom Lightning components (option D). This means creating custom components that use Lightning Web Components or Aura Components frameworks to display report data in Salesforce. A custom component can improve reporting performance by using client-side caching, pagination, lazy loading, or other techniques to optimize data rendering and interaction.

The recommended approach to re-run the test is to refresh the full copy sandbox and re-run the data migration test. A full copy sandbox is a replica of the production Org, including all data, metadata, and attachments. Refreshing a full copy sandbox means creating a new copy of the production Org and replacing the existing sandbox. This would ensure that the test is run on a clean and up-to-date environment, without any leftover data or configuration from previous tests. Truncating or hard deleting objects would not be sufficient, because they would not remove all the data or metadata from the sandbox, and they could also affect other dependent objects or processes.

Data integrity and data usability are two aspects of data that an Enterprise data governance program aims to improve. Data integrity refers to the accuracy, consistency, and validity of the data across the enterprise2. Data usability refers to the ease of access, analysis, and interpretation of the data by the end users

The correct answer is B, add custom indexes on frequently searched account and contact object fields. Custom indexes are a way to improve the performance of yourqueries and reports by creating indexes on specific fields that are often used in filters or joins. By adding custom indexes on frequently searched account and contact object fields, you can speed up the response time for reports and list views. Loading only the data that users are permitted to access, limiting data loading to the 2000 most recent records, or creating a skinny table are also possible solutions, but they are either not feasible, not scalable, or not supported by Salesforce.

 Option C is the best answer because reviewingprojected data storage needs is an important step in designing a field-level audit and recovery plan1. You need to estimate how much data storage you will need in the future and plan accordingly. Option A is not correct because reducing data storage by purging old data may not be sufficient or desirable for backup purposes. Option B is not correct because implementing an AppExchange package may not be customized or compatible with your org’s requirements. Option D is not correct because scheduling a weekly export file may not be frequent or granular enough for field-level audit and recovery.

According to the What is Master Data Management (MDM)? article, some of the data challenges that an MDM tool can solve are data duplication, data accuracy and quality, and data standardization. The article states that “MDM solutions comprise a broad range of data cleansing, transformation, and integration practices. As data sources are added to the system, MDM initiates processes to identify, collect, transform, and repair data. Once the data meets the quality thresholds, schemas and taxonomies are created to help maintain a high-quality master reference.” Therefore, an MDM tool can help NTO eliminate data duplication across different systems, improve data accuracy and quality by removing errors and inconsistencies, and standardize data formats and definitions for better integration and analysis.

The data architect should recommend Lighting platform plus license type for the finance team that best meets the requirements. This license type allows users toaccess custom objects and run reports and dashboards on them, without accessing any sales objects. Option A is incorrect because Service Cloud license type is more suitable for customer service users who need to access cases, knowledge, and other serviceobjects. Option B is incorrect because Sales Cloud license type is more suitable for sales users who need to access accounts, contacts, opportunities, and other sales objects. Option C is incorrect because Light Platform Start license type does not allow users to run reports and dashboards on custom objects.

The best solution to extract 50 million records from a custom object everyday from Salesforce org without facing query timeout issues is to use an ETL tool for extraction of records. ETL stands for extract, transform, and load, and it refers to a process of moving data from one system to another. An ETL tool is a software application that can connect to various data sources, perform data transformations, and load data into a target destination. ETL tools can handle large volumes of data efficiently and reliably, and they often provide features such as scheduling, monitoring, error handling, and logging5. Using a custom auto number and formula field and usethat to chunk records while extracting data is a possible workaround, but it requires creating additional fields and writing complex queries. The REST APIcan extract data as it automatically chunks records by 200, but it has some limitations, such as a maximum of 50 million records per query job6. Asking SF support to increase the query timeout value is not feasible because query timeout values are not configurable

 Skinny tables are custom tables that contain frequently used fields from a standard or custom object. They are used to improve performance by reducing the number of database joins required for queries. Skinny tables have the following characteristics1:

They do not include soft-deleted records, which means they only contain active records and save space.

They avoid resource intensive joins by storing data from multiple objects in one table, which reduces the query time and complexity.

Their tables are kept in sync with their source tables when the source tables are modified, which ensures data consistency and accuracy.

A master-detail field on VTOTime__c to Project__c is the data relationship that the data architect should use to support the requirement when creating the custom VTOTime__c object. A master-detail relationship creates a parent-child relationship between two objects, where the master record controls certain behaviors of the detail record, such as security, ownership, deletion, and roll-up summary fields. By using a master-detail field on VTOTime__c to Project__c, you can ensure that the ability to view or edit the VTOTime__c object is the same as the Project__c record, and that managers can see the total hours volunteered while viewing the Project__c record using a roll-up summary field.

The best solution to make sure decrypted values are exported during data export is to create another field to copy data from encrypted field and use this field in export. This is because classic encryptiondoes not support exporting decrypted values of encrypted fields. The view encrypted data permission only allows users to view decrypted values in the user interface, but not in reports or data exports. Therefore, a workaround is to create a formula field or a workflow field update that copies the value of the encrypted field to another field, and use that field for data export. However, this solution has some drawbacks, such as exposing sensitive data in plain text and consuming extra storage space. A better solution would be to use Shield Platform Encryption, which supports exporting decrypted values of encryptedfields with the Export Encrypted Data permission

To build a custom big object to support storing more than 100 million records in Salesforce, a data architect should use Metadata API or Big Object in setup. Metadata API is an API that allows developers to create, retrieve, update, or delete metadata components in Salesforce programmatically. Big Object in setup is a user interface that allows admins to create big objects declaratively without writing code. Both tools can be used to define custom big objects and their fields, indexes, and relationships in Salesforce. Option A is incorrect because DX (Developer Experience) is a set of tools that allows developers to create and manage applications on Salesforce Platform, but it does not support creating big objects directly. Option D is incorrect because Object Manager in setup is a user interface that allows admins to create and manage standard and custom objects in Salesforce, butit does not support creating big objects declaratively.

Using leading % wildcards, performinglarge loads and deletions, and using NOT and != operators are three options that prevent a query from being selective. These options can cause the query to scan a large number of records or indexes, which can negatively impact the performance and scalability of the query5. Using a custom index on a deterministic formula field, on the other hand, can improve the query selectivity by allowing the query to use the index instead of scanning all the records6.

Cleaning data before importing to Salesforce and using Salesforce matching and duplicate rules are two design considerations that an architect should take to minimize data duplication when migrating legacy account data from two aging systems into Salesforce. Cleaning data before importing involves removing or correcting any inaccurate, incomplete, or inconsistent data from the source systems, as well as identifying and resolving any potential duplicates. This ensures that only high-quality and unique data is imported to Salesforce. Using Salesforce matching and duplicate rules allows the architect to define how Salesforce identifies duplicate records during import and how users can handle them. This prevents or reduces the creation of duplicate records in Salesforce and improves data quality. The other options are not effective or recommended for minimizing data duplication.

Importing Account records first followed by order records after sorting orders by AccountID is the recommended way to avoid locking issues during import. This can reduce the number of lock contention errors by minimizing the number of parent records that are concurrently processed by multiple batches. Sorting orders by AccountID can also group the child records by their parent records and avoid updating the same parent record in different batches3. Importing Account records first followed by order records after sorting order by OrderID will not help with avoiding locking issues because it does not group the child records by their parent records. Changing the relationship toLookup and updating the relationship to master-detail after import will not work because changing a relationship from Lookup to master-detail requires that all child records have a parent record, which may not be the case after import. Importing Order records and Account records separately and populating AccountID in orders using batch Apex will not help with avoiding locking issues because it still requires updating the parent records in batches.

  IP restrictions can be used to prevent users from accessing Salesforce from outside the company network or VPN. According to this article, sharing settings can be used to control access to customer information based on record ownership. According to this article, custom Apex can be used to support customer requests for removal of their information from Salesforce.

Having each system pull the record changes from Salesforce using change data capture (option D) is the correct solution for ensuring all systems using customer data are kept up to date, as it allows the systems to subscribe to real-time events from Salesforce and receive notifications when customer records are created, updated, deleted, or undeleted. Sending customer data nightly to the system of truthin a scheduled batch job (option A) or sending customer record changes from Salesforce to each system in a nightly batch job (option B) are not good solutions, as they may cause data latency and inconsistency, and they do not provide real-time updates. Sending customer record changes from Salesforce to the system of truth in real time (option C) is also not a good solution, as it does not address how the other systems will receive the updates from the system of truth.