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Salesforce Plat-Arch-201 Exam Syllabus Topics:

Section	Weight	Objectives
Data Integration	20%	- 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 synchronization and consistency 1. Conflict resolution, data consistency and idempotency
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 - 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
Large Data Volumes and Performance	20%	- LDV architecture design 1. Data distribution, archiving and partitioning strategies - Query and performance optimization 1. Indexing, selective queries and avoiding performance bottlenecks - 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 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
Data Governance, Quality and Security	15%	- Data security and compliance 1. Access control, encryption, compliance and audit - Data governance framework 1. Policies, standards, ownership and stewardship - Data quality management 1. Profiling, monitoring, cleansing and enrichment

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Salesforce Certified Platform Data Architect Sample Questions (Q155-Q160):

NEW QUESTION # 155
NTO has been using salesforce for sales and service for 10 years. For the past 2 years, the marketing group has noticed a raise from 0 to 35 % in returned mail when sending mail using the contact information stored in salesforce. Which solution should the data architect use to reduce the amount of returned mails?

A. Have the sales team to call all existing customers and ask to verify the contact details.
B. Delete contacts when the mail is returned to save postal cost to NTO.
C. Use a 3rd-party data source to update contact information in salesforce.
D. Email all customer and asked them to verify their information and to call NTO if their address is incorrect.

Answer: C

Explanation:
Using a third-party data source to update contact information in Salesforce is the best solution to reduce the amount of returned mails. This way, the data architect can ensure that the contact information is accurate and up-to-date without relying on manual verification or deletion of contacts

NEW QUESTION # 156
Universal Containers (UC) is implementing its new Internet of Things technology, which consists of smart containers that provide information on container temperature and humidity updated every 10 minutes back to UC. There are roughly 10,000 containers equipped with this technology with the number expected to increase to 50,000 across the next five years. It is essential that Salesforce user have access to current and historical temperature and humidity data for each container. What is the recommended solution?

A. Create new custom fields for temperature and humidity in the existing Container custom object, as well as an external ID field that is unique for each container. These custom fields are updated when a new measure is received.
B. Create a new Container Reading custom object, which is created when a new measure is received for a specific container. The Container Reading custom object has a master-detail relationship to the container object.
C. Create a new Container Reading custom object with a master-detail relationship to Container which is created when a new measure is received for a specific container. Implement an archiving process that runs every hour.
D. Create a new Lightning Component that displays last humidity and temperature data for a specific container and can also display historical trends obtaining relevant data from UC's existing data warehouse.

Answer: C

Explanation:
The recommended solution for Universal Containers (UC) to implement its new Internet of Things technology is to create a new Container Reading custom object with a master-detail relationship to Container which is created when a new measure is received for a specific container.
Implement an archiving process that runs every hour. This solution would allow UC to store and access current and historical temperature and humidity data for each container on Salesforce, and use reports and dashboards to analyze it. However, since UC expects a large volume of data over time, they should implement an archiving process that moves data off-platform after a certain period of time to avoid hitting the Org data storage limit and maintain optimal performance. The other options are not recommended, as they would either not store the historical data on Salesforce, or create too many custom fields on the Container object that could impact performance and usability.

NEW QUESTION # 157
Universal Containers (UC) is in the process of selling half of its company. As part of this split, UC's main Salesforce org will be divided into two org:org A and org B, UC has delivered these requirements to its data architect
1. The data model for Org B will drastically change with different objects, fields, and picklist values.
2. Three million records will need to be migrated from org A to org B for compliance reasons.
3. The migrate will need occur within the next two month, prior to be split.
Which migrate strategy should a data architect use to successfully migrate the date?

A. Use Data Loader for export and Data Import Wizard for import
B. Write a script to use the Bulk API
C. use as ETL tool to orchestrate the migration.
D. Use the Salesforces CLI to query, export, and import

Answer: C

Explanation:
Using an ETL tool to orchestrate the migration is the best strategy for this scenario, as it can handle the data model changes, the large volume of records, and the tight timeline.

NEW QUESTION # 158
UC has large amount of orders coming in from its online portal. Historically all order are assigned to a generic user. Which 2 measures should data architect recommend to avoid any performance issues while working with large number of order records? Choose 2 answer

A. Create a pool of generic users and distribute the assignment of memory to the pool of users.
B. Create a role at top of role hierarchy and assign the role to the generic user.
C. Clear the role field in the generic user record.
D. Salesforce handles the assignment of orders automatically and there is no performance impact.

Answer: B,C

Explanation:
Clearing the role field in the generic user record and creating a role at the top of the role hierarchy and assigning it to the generic user are two measures that can help avoid performance issues while working with large number of order records. These measures can prevent data skew and lock contention that may occur when a single user owns or shares a large number of records

NEW QUESTION # 159
Universal Containers is exporting 40 million Account records from Salesforce using Informatica Cloud. The ETL tool fails and the query log indicates a full table scan time-out failure. What is the recommended solution?

A. Modify the export query with LIMIT clause with Batch size 10,000.
B. Modify the export job header to specify Sforce-Enable-PKChunking.
C. Modify the export query that includes standard index fields(s).
D. Modify the export job header to specify Export-in-Parallel.

Answer: B

Explanation:
The Sforce-Enable-PKChunking header enables you to extract large data sets from Salesforce by using a technique called primary key (PK) chunking. PK chunking splits your query into multiple queries based on the record IDs of the queried object. This reduces the query time and avoids the query timeout issues that can occur with large data volumes

NEW QUESTION # 160
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