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Salesforce Data-Architect Exam Syllabus Topics:

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

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Salesforce Certified Data Architect Sample Questions (Q109-Q114):

NEW QUESTION # 109
Universal Containers (UC) has an Application custom object, which has tens of millions of records created in the past 5 years. UC needs the last 5 years of data to exist in Salesforce at all times for reporting and queries. UC is currently encountering performance issues when reporting and running queries on this Object using date ranges as filters. Which two options can be used to improve report performance?

A. Add custom indexes to the Date fields used for filtering the report.
B. Ask support to create a skinny table for Application with the necessary reporting fields.
C. Add custom indexes to all fields on Application without a standard index.
D. Run multiple reports to get different pieces of the data and combine them.

Answer: A,B

Explanation:
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 queries4. 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

NEW QUESTION # 110
A large insurance provider is looking to implement Salesforce. The following exist.
1. Multiple channel for lead acquisition
2. Duplication leads across channels
3. Poor customer experience and higher costs
On analysis, it found that there are duplicate leads that are resulting to mitigate the issues?

A. Implement third-party solution to clean and event lead data.
B. Implement de-duplication strategy to prevent duplicate leads
C. Build process is manually search and merge duplicates.
D. Standard lead information across all channels.
E. Build a custom solution to identify and merge duplicate leads.

Answer: A,B,D

Explanation:
According to the Salesforce documentation2, duplicate leads are leads that have the same or similar information as other leads in Salesforce. Duplicate leads can cause poor customer experience, higher costs, and inaccurate reporting. To mitigate the issues caused by duplicate leads, some of the recommended practices are:
Standardize lead information across all channels (option B). This means using consistent formats, values, and fields for capturing lead data from different sources, such as web forms, email campaigns, or third-party vendors. This can help reduce data quality issues and make it easier to identify and prevent duplicate leads.
Implement a third-party solution to clean and enrich lead data (option D). This means using an external service or tool that can validate, correct, update, and enhance lead data before or after importing it into Salesforce. This can help improve data quality and accuracy, and reduce duplicate leads.
Implement a de-duplication strategy to prevent duplicate leads (option E). This means using Salesforce features or custom solutions that can detect and block duplicate leads from being created or imported into Salesforce. For example, using Data.com Duplicate Management3, which allows defining matching rules and duplicate rules for leads and other objects.
Building a process to manually search and merge duplicates (option A) is not a good practice, as it can be time-consuming, error-prone, and inefficient. Building a custom solution to identify and merge duplicate leads (option C) is also not a good practice, as it can be complex, costly, and difficult to maintain. It is better to use existing Salesforce features or third-party solutions that can handle duplicate leads more effectively.

NEW QUESTION # 111
UC has millions of Cases and are running out of storage. Some user groups need to have access to historical cases for up to 7 years.
Which 2 solutions should a data architect recommend in order to minimize performance and storage issues?
Choose 2 answers:

A. Leverage on premise data archival and build integration to view archived data.
B. Export data out of salesforce and store in Flat files on external system.
C. Create a custom object to store case history and run reports on it.
D. Leverage big object to archive case data and lightning components to show archived data.

Answer: A,D

Explanation:
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.

NEW QUESTION # 112
Get Cloudy Consulting uses an invoicing system that has specific requirements. One requirement is that attachments associated with the Invoice_c custom object be classified by Types (i.e., ""Purchase Order"", ""Receipt"", etc.) so that reporting can be performed on invoices showing the number of attachments grouped by Type.
What should an Architect do to categorize the attachments to fulfill these requirements?

A. Create a custom picklist field for the Type on the standard Attachment object with the values.
B. Create a custom object related to the Invoice object with a picklist field for the Type.
C. Add a ContentType picklist field to the Attachment layout and create additional picklist options.
D. Add additional options to the standard ContentType picklist field for the Attachment object.

Answer: B

NEW QUESTION # 113
DreamHouse Realty has a legacy system that captures Branch Offices and Transactions. DreamHouse Realty has 15 Branch Offices. Transactions can relate to any Branch Office. DreamHouse Realty has created hundreds of thousands of Transactions per year.
A Data Architect needs to denormalize this data model into a single Transaction object with a Branch Office picklist.
What are two important considerations for the Data Architect in this scenario? (Choose two.)

A. Standard list view in-line editing.
B. Bulk API limitations on picklist fields.
C. Limitations on Org data storage.
D. Limitations on master-detail relationships.

Answer: B,C

Explanation:
The Data Architect should consider the limitations on Org data storage and the Bulk API limitations on picklist fields when denormalizing the data model into a single Transaction object with a Branch Office picklist. The Org data storage limit is the total amount of data that can be stored in a Salesforce Org, and it depends on the edition and license type of the Org1. The Bulk API limit on picklist fields is the maximum number of values that can be imported or exported using the Bulk API, and it is 1,000 values per picklist field2. These limitations could affect the performance and scalability of the data model, and the Data Architect should plan accordingly.

NEW QUESTION # 114
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