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Salesforce Plat-Arch-201 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Data Modeling and Database Design	25%	- Data model design for Customer 360 1. Objects, fields, relationships and object features 2. Scalable design aligned with security and sharing model - Data skew prevention 1. Avoid record locking, sharing issues and excessive parent-child relationships - Object type selection 1. Standard/custom objects vs Big Objects: use cases, pros and cons - Metadata management 1. Business dictionary, data lineage, taxonomy and classification
Topic 2: Large Data Volumes and Performance	20%	- 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
Topic 3: Master Data Management	5%	- MDM implementation approaches 1. Canonical modeling and hierarchy management 2. Harmonization, consolidation, survivorship rules and thresholds - Golden record and system of truth 1. Establishing single source of truth in single org
Topic 4: Data Governance, Quality and Security	15%	- Data quality management 1. Profiling, monitoring, cleansing and enrichment - Data security and compliance 1. Access control, encryption, compliance and audit - Data governance framework 1. Policies, standards, ownership and stewardship
Topic 5: Data Integration	20%	- External data sources 1. External Objects, OData and virtual data access - Data synchronization and consistency 1. Conflict resolution, data consistency and idempotency - Integration patterns and technologies 1. APIs, middleware and external systems integration 2. Synchronous vs asynchronous, batch vs real-time
Topic 6: Data Migration	15%	- Migration execution and tools 1. Data loader, ETL tools and bulk API usage - Data quality and validation 1. Cleaning, deduplication and post-migration verification - Migration strategy and planning 1. Assessment, mapping, validation and rollback planning

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Salesforce Certified Platform Data Architect Sample Questions (Q42-Q47):

NEW QUESTION # 42
What makes Skinny tables fast? Choose three answer

A. Their tables are kept in sync with their source tables when the source tables are modified
B. They do not include soft-deleted records
C. They support up to a max of 100 of columns
D. They can contain fields from other objects
E. They avoid resource intensive joins

Answer: A,B,E

Explanation:
Skinny tables are custom tables that contain frequently used fields from a standard or custom object. They are used to improve performance by reducing the number of database joins required for queries. Skinny tables have the following characteristics:
They do not include soft-deleted records, which means they only contain active records and save space.
They avoid resource intensive joins by storing data from multiple objects in one table, which reduces the query time and complexity.
Their tables are kept in sync with their source tables when the source tables are modified, which ensures data consistency and accuracy.

NEW QUESTION # 43
UC is rolling out Sales App globally to bring sales teams together on one platform. UC expects millions of opportunities and accounts to be creates and is concerned about the performance of the application. Which 3 recommendations should the data architect make to avoid the data skew? Choose 3 answer

A. Limit associating 10000 records looking up to same records.
B. Assign 10000 opportunities to one account.
C. Use picklist fields rather than lookup to custom object.
D. Limit associating 10000 opportunities to one account.
E. Limit assigning one user 10000 records ownership.

Answer: A,D,E

Explanation:
Data skew occurs when a large number of child records are associated with a single parent record, or when a single user owns a large number of records. This can cause performance issues and lock contention. To avoid data skew, the data architect should limit assigning one user
10,000 records ownership, limit associating 10,000 opportunities to one account, and limit associating 10,000 records looking up to the same record

NEW QUESTION # 44
UC has multiple SF orgs that are distributed across regional branches. Each branch stores local customer data inside its org's Account and Contact objects. This creates a scenario where UC is unable to view customers across all orgs. UC has an initiative to create a 360-degree view of the customer, as UC would like to see Account and Contact data from all orgs in one place. What should a data architect suggest to achieve this 360-degree view of the customer?

A. Use an ETL tool to migrate gap Accounts and Contacts into each org.
B. Build a bidirectional integration between all orgs.
C. Consolidate the data from each org into a centralized datastore
D. Use Salesforce Connect's cross-org adapter.

Answer: C

Explanation:
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.

NEW QUESTION # 45
Universal Containers (UC) has over 10 million accounts with an average of 20 opportunities with each account. A Sales Executive at UC needs to generate a daily report for all opportunities in a specific opportunity stage. Which two key considerations should be made to make sure the performance of the report is not degraded due to large data volume?

A. Number of joins used in report query.
B. Number of characters in report query.
C. Number of records returned by report query.
D. Number of queries running at a time.

Answer: A,C

Explanation:
The number of joins used in report query and the number of records returned by report query are two key considerations to make sure the performance of the report is not degraded due to large data volume. The number of joins used in report query affects the complexity and execution time of the query, especially when joining multiple large objects. The number of records returned by report query affects the amount of data that needs to be processed and displayed by the report engine.

NEW QUESTION # 46
UC needs to load a large volume of leads into salesforce on a weekly basis. During this process the validation rules are disabled. What should a data architect recommend to ensure data quality is maintained in salesforce.

A. Activate validation rules once the leads are loaded into salesforce to maintain quality.
B. Ensure the lead data is preprocessed for quality before loading into salesforce.
C. Develop custom APEX batch process to improve quality once the load is completed.
D. Allow validation rules to be activated during the load of leads into salesforce.

Answer: B

Explanation:
Ensuring the lead data is preprocessed for quality before loading into Salesforce is the best way to maintain data quality. Activating validation rules after the load or developing a custom Apex batch process may not catch all the errors or may require additional time and resources. Allowing validation rules to be activated during the load may cause failures or delays.

NEW QUESTION # 47
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