Free DATA-ARCHITECT Exam Dumps Preview

Option B is correct because data model is a key artifact that an architect should use to document the data architecture for a multi-system, enterprise Salesforce implementation 1. Data model describes the structure and relationship of data entities within an organization 2.
Option C is correct because integration specification is another key artifact that an architect should use to document the data architecture for a multi-system, enterprise Salesforce implementation 1. Integration specification defines the scope, requirements, design, testing, and deployment of integration solutions between Salesforce and other systems 3.
Option A is not correct because user stories are not key artifacts for documenting the data architecture, but agile development tools that capture the features and functionalities that users want from a system 4.
Option D is not correct because non-functional requirements are not key artifacts for documenting the data architecture, but quality attributes that specify how well a system performs its functions.

Using an indexed data field with bounded data filters can improve the report performance by making the query more selective and reducing the number of records to scan. Using formula fields to surface information from related entities on the report can also enhance the report performance by avoiding joins and complex calculations

Creating validation rules to check if the required attributes are entered is the best option to mandate this when customers are created in Salesforce. Validation rules allow you to specify criteria that must be met before a record can be saved. You can use validation rules to ensure that customers have a first name, last name, and email when they are created in Salesforce. This way, you can prevent incomplete or invalid data from being sent to your MDM solution.

To improve data quality and avoid data skew, the data architect should create a picklist field with values sorted alphabetically for tracking shipping status on opportunity. A picklist field ensures that only valid values are entered and prevents typos or variations in spelling. Sorting the values alphabetically makes it easier for users to find and select the correct value. Data skew occurs when a large number of records are owned by a single user or have a single value for a field. Creating a picklist field with a limited number of values does not cause data skew, as long as the distribution of values is balanced and not skewed towards one value.

Persistence is the data pattern that will allow a data architect to satisfy the requirements, while also keeping limits in mind. Persistence means storing data from external sources in Salesforce objects, either standard or custom. This allows you to access the data within Salesforce and use it for reporting, analytics, workflows, and other features. Persistence also helps you avoid hitting API limits or performance issues when accessing large volumes of data from external systems. You can use various tools such as Data Loader, Bulk API, or Platform Events to persist IoT data from connected devices to a cloud database in Salesforce.

The data architect should recommend using field metadata attributes for compliance categorization, data owner, and data sensitivity level. This will allow the SF admins to generate reports to manage compliance based on the field metadata attributes that are defined for each data element in SF. Option A is incorrect because using metadata API to extract field attribute information and use the extract to classify and build reports will require additional development effort and may not be up-to-date with the latest changes in SF.
Option C is incorrect because creating a custom object and field to capture necessary compliance information and build custom reports will require additional configuration effort and may not be consistent with the actual data elements in SF.
Option D is incorrect because building reports for field information, then exporting the information to classify and report for audits will require additional manual effort and may not be accurate or timely.

Checking if the current user is NOT the owner by creating a "before delete" trigger can meet the requirement of allowing only the owner of a contact record to delete that contact. A trigger is a piece of Apex code that can execute before or after a record is inserted, updated, deleted, or undeleted. A "before delete" trigger can prevent the deletion of a record by using the addError() method.

Using Salesforce Bulk API in parallel mode can reduce the migration time by processing multiple batches of records simultaneously and leveraging the server resources more efficiently. The Bulk API is designed for loading large amounts of data into Salesforce

The Individual object is a standard object that lets you store details about data privacy and protection preferences for person accounts, contacts, users, and leads. The Individual object can be used to implement a standard communication preference management model for NTO, with relationships to the other objects.

creating multiple similar products and distributing the skew across those products can be a way to mitigate issues related to lookup skew. The article explains that lookup skew happens when a very large number of records are associated with a single record in the lookup object, and this can cause record locking and performance issues. The article suggests creating multiple copies of the same product record and assigning different child records to each copy, so that the number of child records per parent record is reduced.

A Sales KPI Dashboard is one reporting option that Get Cloudy Consulting should consider to understand key relevant performance figures and help managers take corrective actions where appropriate. A Sales KPI Dashboard can display various metrics that indicate the health and effectiveness of the sales team, such as quota attainment, pipeline value, win rate, average deal size, sales cycle length, and more. A Sales KPI Dashboard can also help identify trends, patterns, and areas for improvement.

Consolidating the data from each org into a centralized datastore is the best suggestion to achieve a 360- degree view of the customer. This way, UC can have a single source of truth for all customer data and avoid data silos and inconsistencies. The other options are not feasible because they either require complex integration, additional cost, or data duplication.

PK Chunking can resolve query timeout when running a bulk query on an object with more than 10 million records. PK Chunking is a feature of the Bulk API that splits a query into multiple batches based on the record IDs (primary keys) of the queried object. This can improve the query performance and avoid timeouts by reducing the number of records processed in each batch.

Ask support to create a skinny table for Application with the necessary reporting fields. This is an option that can improve report performance by creating a custom table that contains frequently used fields and copies their values from standard or custom objects. Skinny tables are kept in sync with their source tables and are used in place of them for reports and queries 4. Add custom indexes to the Date fields used for filtering the report. This is another option that can improve report performance by creating custom indexes on fields that are often used as filters or join conditions in reports and queries. Custom indexes can speed up data retrieval and reduce query execution time

An Outbound Message is a native Salesforce feature that allows sending data to an external system without code. It can be configured to include any fields from the source object 3. A Field Set is a collection of fields that can be used in Visualforce pages or Apex classes to dynamically determine the fields to send in an HTTP callout. Both of these approaches meet the requirements of Cloud Kicks.

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, but it does not support creating big objects declaratively.

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 finding and 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

Scheduling a weekly dashboard displaying records that are missing information to be sent to managers for review and using Workflow, Validation Rules, and Force.com code (Apex) to enforce critical business processes are two approaches that an architect should recommend to enforce the new Data Quality Plan for UC's Salesforce data. Scheduling a weekly dashboard can provide a regular and visual way of monitoring the data quality and identifying any gaps or issues that need to be addressed by the managers or users. Using Workflow, Validation Rules, and Apex can provide various ways of enforcing data quality standards and business logic by automating actions, displaying error messages, or executing custom code when users create or edit records. The other options are not suitable or helpful for enforcing the Data Quality Plan, as they would either not provide real-time feedback, not prevent data quality issues, or not leverage the capabilities of Salesforce

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 enterprise 2. Data usability refers to the ease of access, analysis, and interpretation of the data by the end users

Partner community license type is the best option for building a channel sales portal, as it allows external resellers to access lead, opportunity, and order data, as well as run reports and dashboards. Customer community and customer community plus license types are more suitable for customer service portals, while lightning external apps starter license type does not support reports and dashboards

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 encryption does 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 encrypted fields with the Export Encrypted Data permission

According to the official Salesforce guide1, big objects are designed to store and manage massive data volumes within Salesforce without affecting performance. They can be queried by using Async SOQL or standard SOQL, and they can be accessed by using Apex, Visualforce, Lightning components, or APIs. Big objects are ideal for storing data that is used for analytics or reporting purposes, such as the reward program data.
Option A is the correct answer because it allows NTO to create a custom big object in Salesforce that can store the reward program data and make it available for consumption by Einstein Analytics and Discovery.
Option B is incorrect because Einstein cannot connect directly to the point of sales system to capture the reward program data.
Option C is incorrect because Einstein Analytics does not support creating big objects.
Option D is incorrect because custom objects are not suitable for storing large volumes of data.

The Sforce-Enable-PKChunking header enables you to extract large data sets from Salesforce by using a technique called primary key (PK) chunking. PK chunking splits your query into multiple queries based on the record IDs of the queried object. This reduces the query time and avoids the query timeout issues that can occur with large data volumes

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 later 2.
Option B is not correct because workflows are not recommended for calculating summary values, as they can cause performance issues and data skew 3.
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.

A data dictionary is a document that describes the structure, format, and meaning of data entities and attributes. A common technique to build a data dictionary is to use an entity relationship diagram (ERD), which shows the logical relationships between objects and fields in a graphical way. Another technique is to use the Salesforce Metadata API, which allows you to retrieve and deploy the metadata that defines your Salesforce org

The correct answer is C, migrate Notes and Attachment to Enhanced Notes and Files using a migration tool. Enhanced Notes and Files are the new features in Lightning Experience that replace the classic Notes and Attachments. They offer more functionality and security than the classic version. To access them in Lightning Experience, you need to migrate your existing Notes and Attachments using a migration tool provided by Salesforce. Adding Notes and Attachments Related List, manually uploading Notes or Attachments, or doing nothing are not valid solutions, as they will not enable you to use the enhanced features in Lightning Experience.

Implementing duplicate rules (option D) is the best solution to remediate the duplication issue, as it allows the data architect to identify and merge duplicate accounts in Salesforce using native features and tools.
Developing an ETL process that utilizes the merge API to merge the duplicate records (option A) is not a good solution, as it may require more coding and testing effort, and it does not prevent duplicates from being created in Salesforce. Utilizing a data warehouse as the system of truth (option B) is also not a good solution, as it may introduce additional complexity and cost, and it does not address the duplication issue in Salesforce. Extracting the data using data loader and using excel to merge the duplicate records (option C) is also not a good solution, as it may be time-consuming and error-prone, and it does not prevent duplicates from being created in Salesforce.

Implementing a custom big object to store the data is the best recommendation to reduce the performance degradation of the platform, as it allows storing large volumes of data that do not need real-time access or reporting. Custom big objects can be defined using metadata API or developer console, and support up to 1 billion records per object. Creating a custom object or using the standard order object would consume a lot of storage space and impact the performance of queries and reports. Using a standard big object defined by salesforce would not be applicable for order records, as standard big objects are predefined for specific use cases such as audit trails or field history.

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.

The best license to provide these features to the franchisees is the Partner Community license. Partner Community licenses are designed for external users who collaborate with your sales team on deals, such as resellers, distributors, or brokers. Partner Community users can access standard CRM objects, such as accounts, contacts, leads, opportunities, campaigns, and reports. They can also access custom objects and run dashboards 12. Salesforce Sales Cloud license is not a good option because it is intended for internal users who need full access to standard CRM and custom apps. Lightning Platform license is not a good option because it is intended for users who need access to custom apps but not to standard CRM functionality. Customer Community license is not a good option because it is intended for external users who need access to customer support features, such as cases and knowledge articles, but not to sales features

Enabling field history tracking on the Case object is the first step to implement a reporting solution to measure the support reps case closure rates. Field history tracking allows you to track changes to certain fields on the Case object, such as Status, Owner, or Priority. You can then create reports based on the field history data to analyze how long it took to close a case, how many times the case owner changed, or how many cases were escalated.

Creating a duplicate rule for account, lead, and contact, using standard matching rules for these objects, and setting the action to report and alert for both creates and edits can help UC fix the issue immediately by prompting users about a record that possibly exists in Salesforce. This can also generate a report regarding duplicate records that can be used for further analysis and resolution

The best design pattern to satisfy the requirement of accessing order data from an on-premise database with REST API access without consuming SF storage limits is to use SF Connect to virtualize the data in SF and avoid storage limits. SF Connect is an integration tool that allows users to access and integrate data from external sources using external objects. External objects are similar to custom objects, except that the data resides in another system and is accessed in real time via web service callouts. SF Connect supports various adapters to connect to different types of external data sources, such as OData, cross-org, or Apex custom adapter 11. Migrate and persist the data in SF to take advantage of native functionality is not a good option because it would consume SF storage limits and require data synchronization between systems.
Develop a bidirectional integration between the on-premise system and Salesforce is not a good option because it would be complex and costly to implement and maintain, and it would also consume SF storage limits. Build a UI for the on-premise system and iframe it in Salesforce is not a good option because it would not provide a seamless user experience and it would not allow users to search, report, or perform actions on the external data.

Leverage an External ID from source system orders to import related order lines. This is the recommended solution because it allows you to use the upsert operation to match records based on the External ID field, which is indexed and unique. This avoids the need to query the parent order IDs in Salesforce before importing the order line items, which can cause time-out errors or long delays 1.

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.

Doing client-side validation of phone number and email field formats and preferring picklist form fields over free text fields, where possible, are two techniques that will help maintain a high level of data quality when designing forms that create Lead records in Salesforce using the REST API. Client-side validation can ensure that the input data is in the correct format and prevent errors or invalid values from being submitted.
Picklist form fields can provide a predefined set of values for the users to choose from and avoid typos or inconsistencies in the data.

Using Bulk API to export 1 million records from Salesforce is the best option. Bulk API is a RESTful API that allows you to perform asynchronous operations on large sets of data. You can use Bulk API to create, update, delete, or query millions of records in batches. Bulk API is optimized for performance and scalability, and it can handle complex data loading scenarios.

Data Loader uses external Id fields to match records in the CSV file with records in Salesforce during an upsert operation. If the CSV file contains duplicate external Id values within the same file, Data Loader will throw an error saying "Duplicate Id Specified" and will not process those records. Therefore, it is important to ensure that the CSV file does not have any duplicate external Id values before using Data Loader to upsert records.

Exploring external data sources in Salesforce to build 360 view of customer is the best strategy to satisfy the requirement, as it allows real-time access to data from other systems without storing it in Salesforce3.
Using a customer data mart may not provide real-time information or may require additional integration efforts. Migrating customer activities from all 4 systems into Salesforce may exceed the storage limits or cause data quality issues. Periodically uploading summary information in Salesforce may not provide current or detailed information.