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Salesforce Data-Architect Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Data Integration and Master Data Management	10%	- Master data management 1. Data synchronization and consistency 2. Single source of truth design 3. MDM strategy and implementation - Integration patterns and tools 1. REST, SOAP, and Bulk API usage 2. Real-time vs batch integration 3. External data sources and objects
Topic 2: Data Governance and Compliance	20%	- Data governance framework 1. Compliance and regulatory requirements 2. Data quality standards 3. Data stewardship and ownership - Data lifecycle management 1. Data classification and handling 2. Data privacy and security 3. Data retention and archiving policies
Topic 3: Data Modeling and Database Design	25%	- Design scalable data models 1. Data model optimization for performance 2. Object relationships and cardinality 3. Custom and standard object design - Indexing and data structure 1. Query optimization strategies 2. Standard and custom indexes 3. Skinny tables and big objects
Topic 4: Salesforce Data Management	25%	- Sharing and visibility design 1. Data access and security model 2. Sharing rules, manual sharing, Apex sharing 3. Organization-wide defaults, role hierarchy - Data import and export strategies 1. Tools: Data Loader, Import Wizard, Bulk API 2. Migration planning and execution 3. Data validation and cleansing
Topic 5: Large Data Volume Considerations	20%	- Storage and optimization 1. Archiving and off-platform storage 2. Performance tuning techniques 3. Storage limits and management - Performance and scalability 1. Handling millions of records 2. Avoiding and resolving data skew 3. Governor limits and bulk processing

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Salesforce Certified Data Architect Sample Questions (Q213-Q218):

NEW QUESTION # 213
DreamHouse Realty has a data model as shown in the image. The Project object has a private sharing model, and it has Roll-Up summary fields to calculate the number of resources assigned to the project, total hours for the project, and the number of work items associated to the project.
There will be a large amount of time entry records to be loaded regularly from an external system into Salesforce.

What should the Architect consider in this situation?

A. Load all data after deferring sharing calculations.
B. Calculate summary values instead of Roll-Up by using triggers.
C. Calculate summary values instead of Roll-Up by using workflow.
D. Load all data using external IDs to link to parent records.

Answer: A

Explanation:
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.

NEW QUESTION # 214
A company has 12 million records, and a nightly integration queries these records.
Which two areas should a Data Architect investigate during troubleshooting if queries are timing out? (Choose two.)

A. Modify the integration users' profile to have View All Data.
B. Create custom indexes on the fields used in the filter criteria.
C. Make sure the query doesn't contain NULL in any filter criteria.
D. Create a formula field instead of having multiple filter criteria.

Answer: B,C

Explanation:
Making sure the query does not contain NULL in any filter criteria can avoid full table scans and leverage indexes more efficiently. Queries with NULL filters are not selective and can cause performance issues. Creating custom indexes on the fields used in the filter criteria can also enhance the query performance by reducing the number of records to scan.

NEW QUESTION # 215
Universal Container (US) is replacing a home grown CRM solution with Salesforce, UC has decided to migrate operational (Open and active) records to Salesforce, while keeping historical records in legacy system, UC would like historical records to be available in Salesforce on an as needed basis.
Which solution should a data architect recommend to meet business requirement?

A. Leverage real-time integration to pull records into Salesforce.
B. Build a chair solution to go the legacy system and display records.
C. Bring all data Salesforce, and delete it after a year.
D. Leverage mashup to display historical records in Salesforce.

Answer: D

NEW QUESTION # 216
Universal Containers (UC) provides shipping services to its customers. They use Opportunities to track customer shipments. At any given time, shipping status can be one of the 10 values. UC has 200,000 Opportunity records. When creating a new field to track shipping status on opportunity, what should the architect do to improve data quality and avoid data skew?

A. Create a Lookup to custom object ShippingStatus c.
B. Create a picklist field, values sorted alphabetically.
C. Create a text field and make it an external I
D. Create a Master -Detail to custom object ShippingStatus c.

Answer: B

NEW QUESTION # 217
Universal Containers (UC) uses the following Salesforce products:
Sales Cloud for customer management.
Marketing Cloud for marketing.
Einstein Analytics for business reporting.
UC occasionally gets a list of prospects from third-party source as comma-separated values (CSV) files for marketing purposes. Historically, UC would load contact Lead object in Salesforce and sync to Marketing Cloud to send marketing communications. The number of records in the Lead object has grown over time and has been consuming large amounts of storage in Sales Cloud, UC is looking for recommendations to reduce the storage and advice on how to optimize the marketing Cloud to send marketing communications. The number of records in the Lead object has grown over time and has been consuming large amounts of storage in Sales Cloud, UC is looking for recommendations to reduce the storage and advice on how to optimize the marketing process.
What should a data architect recommend to UC in order to immediately avoid storage issues in the future?

A. Load the CSV files in an external database and sync with Marketing Cloud prior to sending marketing communications.
B. Load the contacts directly to Marketing Cloud and have a reconciliation process to track prospects that are converted to customers.
C. Load the CSV files in Einstein Analytics and sync with Marketing Cloud prior to sending marketing communications;
D. Continue to use the existing process to use Lead object to sync with Marketing Cloud and delete Lead records from Sales after the sync is complete.

Answer: B

Explanation:
According to the Salesforce documentation4, Marketing Cloud is a platform that allows creating and managing marketing campaigns across multiple channels, such as email, mobile, social media, web, etc. Marketing Cloud can integrate with Sales Cloud and other Salesforce products to share data and insights. One of the ways to integrate Marketing Cloud with Sales Cloud is using Marketing Cloud Connect5, which allows syncing data between the two platforms using synchronized data sources.
However, if UC occasionally gets a list of prospects from third-party sources as CSV files for marketing purposes, it may not be necessary or efficient to load them into Sales Cloud first and then sync them with Marketing Cloud. This can consume large amounts of storage in Sales Cloud, which has a limit based on the license type6. It can also cause data quality issues, such as duplicates or outdated information.
A better option for UC is to load the contacts directly to Marketing Cloud using Import Definition, which allows importing data from external files or databases into Marketing Cloud data extensions. Data extensions are custom tables that store marketing data in Marketing Cloud. This way, UC can avoid storage issues in Sales Cloud and optimize the marketing process by sending marketing communications directly from Marketing Cloud.
To track prospects that are converted to customers, UC can have a reconciliation process that compares the contacts in Marketing Cloud with the accounts or contacts in Sales Cloud. This can be done using SQL queries or API calls to access and compare data from both platforms. Alternatively, UC can use Marketing Cloud Connect to sync the converted contacts from Sales Cloud to Marketing Cloud using synchronized data sources.
Loading the CSV files in Einstein Analytics and syncing with Marketing Cloud prior to sending marketing communications (option A) is not a good option, as it can add unnecessary complexity and latency to the process. Einstein Analytics is a platform that allows creating and analyzing data using interactive dashboards and reports. It is not designed for importing and exporting data for marketing purposes.
Loading the CSV files in an external database and syncing with Marketing Cloud prior to sending marketing communications (option B) is also not a good option, as it can incur additional costs and maintenance for the external database. It can also introduce data security and privacy risks, as the data may not be encrypted or protected by Salesforce.
Continuing to use the existing process to use Lead object to sync with Marketing Cloud and delete Lead records from Sales after the sync is complete (option D) is not a good option, as it can cause performance issues and data loss. Deleting Lead records from Sales can affect reporting and auditing, as well as trigger workflows and validations that may not be intended. It can also cause data inconsistency and synchronization errors between Sales Cloud and Marketing Cloud.

NEW QUESTION # 218
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