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| Section | Weight | Objectives |
|---|
| Data Governance, Quality and Security | 15% | - Data quality management
- 1. Profiling, monitoring, cleansing and enrichment
- Data governance framework
- 1. Policies, standards, ownership and stewardship
- Data security and compliance
- 1. Access control, encryption, compliance and audit
|
| Large Data Volumes and Performance | 20% | - Query and performance optimization
- 1. Indexing, selective queries and avoiding performance bottlenecks
- LDV architecture design
- 1. Data distribution, archiving and partitioning strategies
- Storage and scalability planning
- 1. Data volume growth planning and storage limits
|
| Master Data Management | 5% | - Golden record and system of truth
- 1. Establishing single source of truth in single org
- MDM implementation approaches
- 1. Harmonization, consolidation, survivorship rules and thresholds
- 2. Canonical modeling and hierarchy management
|
| Data Integration | 20% | - Data synchronization and consistency
- 1. Conflict resolution, data consistency and idempotency
- External data sources
- 1. External Objects, OData and virtual data access
- Integration patterns and technologies
- 1. Synchronous vs asynchronous, batch vs real-time
- 2. APIs, middleware and external systems integration
|
| Data Modeling and Database Design | 25% | - Data skew prevention
- 1. Avoid record locking, sharing issues and excessive parent-child relationships
- Data model design for Customer 360
- 1. Scalable design aligned with security and sharing model
- 2. Objects, fields, relationships and object features
- Metadata management
- 1. Business dictionary, data lineage, taxonomy and classification
- Object type selection
- 1. Standard/custom objects vs Big Objects: use cases, pros and cons
|
| Data Migration | 15% | - Migration execution and tools
- 1. Data loader, ETL tools and bulk API usage
- Migration strategy and planning
- 1. Assessment, mapping, validation and rollback planning
- Data quality and validation
- 1. Cleaning, deduplication and post-migration verification
|
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Salesforce Certified Platform Data Architect Sample Questions (Q140-Q145):
NEW QUESTION # 140
UC recently migrated 1 Billion customer related records from a legacy data store to Heroku Postgres. A subset of the data need to be synchronized with salesforce so that service agents are able to support customers directly within the service console. The remaining non- synchronized set of data will need to be accessed by salesforce at any point in time, but UC management is concerned about storage limitations. What should a data architect recommend to meet these requirements with minimal effort?
- A. Migrate the data to big objects and leverage async SOQL with custom objects.
- B. Use Heroku connect to bi-directional, sync all data between systems.
- C. As needed, make call outs into Heroku postgres and persist the data in salesforce.
- D. Virtualize the remaining set of data with salesforce connect and external objects.
Answer: D
Explanation:
Virtualizing the remaining set of data with salesforce connect and external objects is the best way to meet the requirements with minimal effort, as it allows salesforce to access data stored in Heroku Postgres without storing it in salesforce. This reduces the storage limitations and avoids data duplication. Heroku connect can bi-directionally sync data between systems, but it requires more configuration and maintenance. Making callouts to Heroku Postgres and persisting the data in salesforce may not be feasible for 1 billion records. Migrating the data to big objects may incur additional costs and require custom code to use async SOQL
NEW QUESTION # 141
What should a data architect do to provide additional guidance for users when they enter information in a standard field?
- A. Add a label field with help text adjacent to the custom field.
- B. Provide custom help text under field properties.
- C. Add custom help text in default value for the field.
- D. Create a custom page with help text for user guidance.
Answer: B
Explanation:
The correct answer is A. To provide additional guidance for users when they enter information in a standard field, a data architect should provide custom help text under field properties. This will display a help icon next to the field label that users can hover over to see the help text.
NEW QUESTION # 142
Universal Containers (UC) has 1,000 accounts and 50,000 opportunities. UC has an enterprise security requirement to export all sales data outside of Salesforce on a weekly basis. The security requirement also calls for exporting key operational data that includes events such as file downloads, logins, logouts, etc. Which two recommended approaches would address the above requirement?
- A. Use Event Monitoring to extract event data to on-premise systems.
- B. Use a custom built extract job to extract operational data to on-premise systems.
- C. Use Field Audit History to capture operational data and extract it to on-premise systems.
- D. Use Weekly Export to extract transactional data to on-premise systems.
Answer: A,D
Explanation:
Using Weekly Export to extract transactional data to on-premise systems and using Event Monitoring to extract event data to on-premise systems are two recommended approaches that would address the security requirement of UC. Weekly Export is a built-in feature that allows UC to download a zip file of their Salesforce data on a weekly basis. Event Monitoring is a tool that allows UC to access detailed information about various events that occur in their Salesforce org, such as logins, logouts, file downloads, etc.
NEW QUESTION # 143
A large retail B2C customer wants to build a 360 view of its customer for its call center agents.
The customer interaction is currently maintained in the following system:
1. Salesforce CRM
2. Custom billing solution
3. Customer Master Data management (MDM)
4. Contract Management system
5. Marketing solution
What should a data architect recommend that would help upgrade uniquely identify customer across multiple systems:
- A. Store the salesforce id in all the solutions to identify the customer.
- B. Create a custom field as external id to maintain the customer Id from the MDM solution.
- C. Create a custom object that will serve as a cross reference for the customer id.
- D. Create a customer data base and use this id in all systems.
Answer: B
Explanation:
To help uniquely identify customer across multiple systems, a data architect should recommend creating a custom field as external ID to maintain the customer ID from the MDM solution. An external ID is a custom field that has the "External ID" attribute enabled, which means that it contains unique record identifiers from a system outside of Salesforce. By using the customer ID from the MDM solution as an external ID in Salesforce CRM, Contract Management system, and Marketing solution, the data architect can ensure that each customer can be easily identified and integrated across these systems.
NEW QUESTION # 144
UC has one SF org (Org A) and recently acquired a secondary company with its own Salesforce org (Org B). UC has decided to keep the orgs running separately but would like to bidirectionally share opportunities between the orgs in near-real time. Which 3 options should a data architect recommend to share data between Org A and Org B? Choose 3 answer
- A. Install a 3rd party AppExchange tool to handle the data sharing
- B. Leverage Heroku Connect and Heroku Postgres to bidirectionally sync Opportunities.
- C. Use Salesforce Connect and the cross-org adapter to visualize Opportunities into external objects
- D. Develop an Apex class that pushes opportunity data between orgs daily via the Apex schedule.
- E. Leverage middleware tools to bidirectionally send Opportunity data across orgs.
Answer: B,C,E
Explanation:
Leveraging Heroku Connect and Heroku Postgres, middleware tools, or Salesforce Connect and the cross-org adapter are all viable options to share data between Org A and Org B in near-real time. Installing a 3rd party AppExchange tool may not provide bidirectional sync or may have additional costs. Developing an Apex class that pushes opportunity data between orgs daily via the Apex schedule may not meet the near-real time requirement.
NEW QUESTION # 145
......
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