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Salesforce Plat-Arch-201 Exam Syllabus Topics:

SectionWeightObjectives
Data Governance, Quality and Security15%- Data governance framework
  • 1. Policies, standards, ownership and stewardship
- Data quality management
  • 1. Profiling, monitoring, cleansing and enrichment
- Data security and compliance
  • 1. Access control, encryption, compliance and audit
Data Migration15%- Migration strategy and planning
  • 1. Assessment, mapping, validation and rollback planning
- Migration execution and tools
  • 1. Data loader, ETL tools and bulk API usage
- Data quality and validation
  • 1. Cleaning, deduplication and post-migration verification
Large Data Volumes and Performance20%- Storage and scalability planning
  • 1. Data volume growth planning and storage limits
- LDV architecture design
  • 1. Data distribution, archiving and partitioning strategies
- Query and performance optimization
  • 1. Indexing, selective queries and avoiding performance bottlenecks
Master Data Management5%- MDM implementation approaches
  • 1. Harmonization, consolidation, survivorship rules and thresholds
  • 2. Canonical modeling and hierarchy management
- Golden record and system of truth
  • 1. Establishing single source of truth in single org
Data Integration20%- External data sources
  • 1. External Objects, OData and virtual data access
- Integration patterns and technologies
  • 1. APIs, middleware and external systems integration
  • 2. Synchronous vs asynchronous, batch vs real-time
- Data synchronization and consistency
  • 1. Conflict resolution, data consistency and idempotency
Data Modeling and Database Design25%- Object type selection
  • 1. Standard/custom objects vs Big Objects: use cases, pros and cons
- Data skew prevention
  • 1. Avoid record locking, sharing issues and excessive parent-child relationships
- Data model design for Customer 360
  • 1. Objects, fields, relationships and object features
  • 2. Scalable design aligned with security and sharing model
- Metadata management
  • 1. Business dictionary, data lineage, taxonomy and classification

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Salesforce Certified Platform Data Architect Sample Questions (Q63-Q68):

NEW QUESTION # 63
Northern Trail Outfitters is concerned because some of its data is sensitive and needs to be identified for access. What should be used to provide ways to filter and identify the sensitive data?

Answer: C

Explanation:
According to the official Salesforce guide, data classification metadata is a feature that allows administrators to classify data fields based on their sensitivity level, such as confidential, restricted, or general. Data classification metadata can be used to filter and identify sensitive data fields and apply appropriate security measures, such as encryption, masking, or auditing. Option D is the correct answer because it suggests using data classification metadata to provide ways to filter and identify sensitive data.


NEW QUESTION # 64
What is an advantage of using Custom metadata type over Custom setting?

Answer: A

Explanation:
Custom metadata records are deployable using packages, which makes them easier to migrate from one environment to another. Custom settings records are not deployable using packages, and they are copied from production to sandbox. Custom metadata types are not available for reporting, and custom metadata records are not editable in Apex.


NEW QUESTION # 65
Get Cloudy Consulting is migrating their legacy system's users and data to Salesforce. They will be creating 15,000 users, 1.5 million Account records, and 15 million Invoice records. The visibility of these records is controlled by a 50 owner and criteria-based sharing rules. Get Cloudy Consulting needs to minimize data loading time during this migration to a new organization.
Which two approaches will accomplish this goal? (Choose two.)

Answer: A,C

Explanation:
Creating the users, uploading all data, and then deploying the sharing rules will reduce the number of sharing recalculations that occur during the data load. Deferring sharing calculations until the data has finished uploading will also improve the performance by postponing the sharing rule evaluation. These are the recommended best practices for loading large data sets into Salesforce


NEW QUESTION # 66
UC has migrated its Back-office data into an on-premise database with REST API access. UC recently implemented Sales cloud for its sales organization. But users are complaining about a lack of order data inside SF. UC is concerned about SF storage limits but would still like Sales cloud to have access to the data. Which design patterns should a data architect select to satisfy the requirement?

Answer: D

Explanation:
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. 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.


NEW QUESTION # 67
Universal Containers is establishing a call center that will use Salesforce. UC receives 10 million calls and creates 100 million cases every month. Cases are linked to a custom call object using lookup relationship. UC would like to run reports and dashboard to better understand different case types being created on calls to better serve customers. What solution should a data architect recommend to meet the business requirement?

Answer: C

Explanation:
According to this article, big objects can store and manage massive amounts of data on the Salesforce platform. This can help UC to archive records from other objects or bring massive datasets from outside systems into a big object. According to this article, Einstein Analytics can be used to create dashboards and lenses to analyze big object data and get insights from advanced AI-driven analytics.


NEW QUESTION # 68
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