Plat-Arch-201学習教材、Plat-Arch-201教育資料

Plat-Arch-201テストガイドの言語は理解しやすいため、学習障害のない学習者は、学生であろうと現職のスタッフであろうと、初心者であれ、多くの経験豊富な経験豊富なスタッフであれ、年。 Plat-Arch-201試験問題は、教育レベルに依存しないすべての分野のすべての人に適用されます。したがって、困難なテストを通過するためにPlat-Arch-201ガイドトレントを選択して合格することは素晴らしい素晴らしいアイデアです。

Salesforce Plat-Arch-201 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Master Data Management	5%	- 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
Topic 2: 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
Topic 3: Data Migration	15%	- 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
Topic 4: Large Data Volumes and Performance	20%	- Storage and scalability planning 1. Data volume growth planning and storage limits - Query and performance optimization 1. Indexing, selective queries and avoiding performance bottlenecks - LDV architecture design 1. Data distribution, archiving and partitioning strategies
Topic 5: Data Modeling and Database Design	25%	- Object type selection 1. Standard/custom objects vs Big Objects: use cases, pros and cons - 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 - Metadata management 1. Business dictionary, data lineage, taxonomy and classification
Topic 6: Data Integration	20%	- Integration patterns and technologies 1. Synchronous vs asynchronous, batch vs real-time 2. APIs, middleware and external systems integration - External data sources 1. External Objects, OData and virtual data access - Data synchronization and consistency 1. Conflict resolution, data consistency and idempotency

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Salesforce Certified Platform Data Architect 認定 Plat-Arch-201 試験問題 (Q76-Q81):

質問 # 76
North Trail Outfitters (NTO) operates a majority of its business from a central Salesforce org, NTO also owns several secondary orgs that the service, finance, and marketing teams work out of, At the moment, there is no integration between central and secondary orgs, leading to data- visibility issues.
Moving forward, NTO has identified that a hub-and-spoke model is the proper architect to manage its data, where the central org is the hub and the secondary orgs are the spokes.
Which tool should a data architect use to orchestrate data between the hub org and spoke orgs?

A. A middleware solution that extracts and distributes data across both the hub and spokes.
B. Develop custom APIs to poll the spoke for change data and push into the org.
C. Develop custom APIs to poll the hub org for change data and push into the spoke orgs.
D. A backup and archive solution that extracts and restores data across orgs.

正解：A

解説：
According to the Salesforce documentation, a hub-and-spoke model is an integration architecture pattern that allows connecting multiple Salesforce orgs using a central org (hub) and one or more secondary orgs (spokes). The hub org acts as the master data source and orchestrates the data flow between the spoke orgs. The spoke orgs act as the consumers or producers of the data and communicate with the hub org.
To orchestrate data between the hub org and spoke orgs, a data architect should use:
A middleware solution that extracts and distributes data across both the hub and spokes (option A). This means using an external service or tool that can connect to multiple Salesforce orgs using APIs or connectors, and perform data extraction, transformation, and distribution operations between the hub and spoke orgs. This can provide a scalable, flexible, and reliable way to orchestrate data across multiple orgs.

質問 # 77
Universal Containers has defined a new Data Quality Plan for their Salesforce data and wants to know how they can enforce it throughout the organization. Which two approaches should an architect recommend to enforce this new plan? Choose 2 answer

A. Schedule a weekly dashboard displaying records that are missing information to be sent to managers for review.
B. Schedule reports that will automatically catch duplicates and merge or delete the records every week.
C. Use Workflow, Validation Rules, and Force.com code (Apex) to enforce critical business processes.
D. Store all data in an external system and set up an integration to Salesforce for view -only access.

正解：A、C

解説：
Scheduling a weekly dashboard displaying records that are missing information to be sent to managers for review and using Workflow, Validation Rules, and Force.com code (Apex) to enforce critical business processes are two approaches that an architect should recommend to enforce the new Data Quality Plan for UC's Salesforce data. Scheduling a weekly dashboard can provide a regular and visual way of monitoring the data quality and identifying any gaps or issues that need to be addressed by the managers or users. Using Workflow, Validation Rules, and Apex can provide various ways of enforcing data quality standards and business logic by automating actions, displaying error messages, or executing custom code when users create or edit records. The other options are not suitable or helpful for enforcing the Data Quality Plan, as they would either not provide real-time feedback, not prevent data quality issues, or not leverage the capabilities of Salesforce

質問 # 78
Northern trail Outfitters (NTO) uses Sales Cloud and service Cloud to manage sales and support processes. Some of NTOs team are complaining they see new fields on their page unsure of which values need be input. NTO is concerned about lack of governance in making changes to Salesforce. Which governance measure should a data architect recommend to solve this issue?

A. Add description fields to explain why the field is used, and mark the field as required.
B. Create validation rules with error messages to explain why the fields is used
C. Create reports to identify which users are leaving blank, and use external data sources o agreement the missing data.
D. Create and manage a data dictionary and ups a governance process for changes made to common objects.

正解：D

解説：
To solve the issue of lack of governance in making changes to Salesforce, a data architect should recommend creating and managing a data dictionary and setting up a governance process for changes made to common objects. A data dictionary is a document that defines the metadata, structure, and relationship of each object and field in Salesforce. A governance process is a set of rules and procedures that govern how changes are proposed, reviewed, approved, and deployed in Salesforce. These measures will help NTO to maintain consistency, quality, and clarity of their data model and avoid confusion and errors among users.

質問 # 79
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 job header to specify Export-in-Parallel.
B. Modify the export query that includes standard index fields(s).
C. Modify the export job header to specify Sforce-Enable-PKChunking.
D. Modify the export query with LIMIT clause with Batch size 10,000.

正解：C

解説：
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

質問 # 80
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. Virtualize the remaining set of data with salesforce connect and external objects.
B. Use Heroku connect to bi-directional, sync all data between systems.
C. Migrate the data to big objects and leverage async SOQL with custom objects.
D. As needed, make call outs into Heroku postgres and persist the data in salesforce.

正解：A

解説：
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

質問 # 81
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