Salesforce Plat-Arch-201 Exam | Plat-Arch-201科目対策 -高品質なPlat-Arch-201日本語版問題解説あなたのため

Plat-Arch-201学習テストは、シラバスの変更と、Salesforce歴史的な質問や業界の動向に基づいた理論と実践の最新の進展に応じて、何百人もの専門家によって改訂された高品質の製品でした。 あなたが学生であろうとオフィスワーカーであろうと、ルーキーであろうと長年の経験を積んだベテランであろうと、Plat-Arch-201ガイドトレントが最適です。 Plat-Arch-201学習教材の主な利点は、98％以上のSalesforce Certified Platform Data Architect高い合格率であり、Plat-Arch-201試験に合格するには十分です。

Salesforce Plat-Arch-201 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Data Integration20%- 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
- External data sources
  • 1. External Objects, OData and virtual data access
Topic 2: 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
Topic 3: Large Data Volumes and Performance20%- 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
Topic 4: 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
Topic 5: Data Modeling and Database Design25%- 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
- 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
Topic 6: Data Governance, Quality and Security15%- 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

>> Plat-Arch-201科目対策 <<

ハイパスレートのPlat-Arch-201科目対策 & 合格スムーズPlat-Arch-201日本語版問題解説 | 高品質なPlat-Arch-201最新テスト

Plat-Arch-201試験に実際に参加して資料を選択する前に、このような証明書を保持することの重要性を思い出してください。このようなPlat-Arch-201証明書を取得することで、昇給、昇進の機会、上司や同僚からの信頼など、将来の多くの同意結果を習得できます。これらすべての快い結果は、もはやあなたにとって夢ではありません。そして、Plat-Arch-201試験準備により、成績を改善し、生活の状態を変え、キャリアの驚くべき変化を得ることができ、すべてが可能になります。それはすべて、Plat-Arch-201学習の質問から始まります。

Salesforce Certified Platform Data Architect 認定 Plat-Arch-201 試験問題 (Q10-Q15):

質問 # 10
Universal Containers (UC) is migrating from a legacy system to Salesforce CRM, UC is concerned about the quality of data being entered by users and through external integrations.
Which two solutions should a data architect recommend to mitigate data quality issues?

正解：B、D

解説：
According to the Salesforce documentation, data quality is the measure of how well the data in Salesforce meets the expectations and requirements of the users and stakeholders. Data quality can be affected by various factors, such as data entry errors, data duplication, data inconsistency, data incompleteness, data timeliness, etc. To mitigate data quality issues, some of the recommended solutions are:
Leverage picklist and lookup fields where possible (option A). This means using fields that restrict the values or references that can be entered by the users or integrations. This can help reduce data entry errors, enforce data consistency, and improve data accuracy.
Leverage validation rules and workflows (option C). This means using features that allow defining ules and criteria to validate the data that is entered or updated by the users or integrations. This can help prevent invalid or incorrect data from being saved, and trigger actions or alerts to correct or improve the data.


質問 # 11
What is a key cause of ownership data skew?

正解：C

解説：
Ownership skew occurs when one user owns a large number of records, affecting performance.


質問 # 12
Universal Containers is creating a new B2C service offering for consumers to ship goods across continents. This is in addition to their well-established B2B offering. Their current Salesforce org uses the standard Account object to track B2B customers. They are expecting to have over
50,000,000 consumers over the next five years across their 50 business regions. B2C customers will be individuals. Household data is not required to be stored. What is the recommended data model for consumer account data to be stored in Salesforce?

正解：B

解説：
The recommended data model for consumer account data to be stored in Salesforce is to use the Account object with Person Accounts and a new B2C page layout. Person Accounts are a special type of accounts that allow you to store information about individual consumers who are not associated with a business account. Person Accounts have the following advantages:
They allow you to use the same standard objects and features that you use for business accounts, such as contacts, opportunities, cases, etc.
They enable you to create different page layouts and record types for B2C and B2B customers, which allows you to customize the user interface and business logic for each segment.
They support large data volumes and can scale up to 50 million records or more, which meets the expected growth of consumers over the next five years.


質問 # 13
US has released a new disaster recovery (DR)policy that states that cloud solutions need a business continuity plan in place separate from the cloud providers built in data recovery solution.
Which solution should a data architect use to comply with the DR policy?

正解：D

解説：
The best solution to comply with the DR policy is to leverage a 3rd party tool that extract Salesforce data/metadata and stores the information in an external protected system. This solution can help create a backup of Salesforce data and metadata in case of a disaster or data loss event. It can also help restore data from the backup system to Salesforce if needed. There are various 3rd party tools available in the AppExchange or online that offer data backup and recovery services for Salesforce. Leverage Salesforce weekly exports and store data in flat files on a protected system is not a good solution because it does not include metadata backup and it does not allow granular or automated data recovery. Utilize an ETL tool to migrate data to an on- premise archive solution is not a good solution because it does not include metadata backup and it may require complex data transformations and synchronizations. Write a custom batch job to extract data changes nightly and store in an external protected system is not a good solution because it does not include metadata backup and it may have performance or reliability issues.


質問 # 14
Northern Trail Outfitter has implemented Salesforce for its associates nationwide, Senior management is concerned that the executive dashboard is not reliable for their real-time decision- making. On analysis, the team the following issues with data entered in Salesforce.
- Information in certain records is incomplete.
- Incorrect entry in certain fields causes records to be excluded in
report fitters.
- Duplicate entries cause incorrect counts.
Which three steps should a data architect recommend to address the issues?

正解：A、B、D

解説：
According to the Salesforce documentation, data quality is the measure of how well the data in Salesforce meets the expectations and requirements of the users and stakeholders. Data quality can be affected by various factors, such as data entry errors, data duplication, data inconsistency, data incompleteness, data timeliness, etc. To address the issues with data quality that affect the reliability of executive dashboards, a data architect should recommend:
Building a sales data warehouse with purpose-built data marts for dashboards and senior management reporting (option B). This means creating a separate database or system that stores and organizes sales data from Salesforce and other sources for analytical purposes. A data warehouse can provide a single source of truth for sales data and enable faster and more accurate reporting and analysis. A data mart is a subset of a data warehouse that focuses on a specific subject or business area, such as sales performance, customer segmentation, product profitability, etc. A data mart can provide tailored and relevant data for different users or groups based on their needs and interests.
Exploring third-party data providers to enrich and augment information entered in Salesforce (option C). This means using external services or tools that can validate, correct, update, and enhance the data that is entered or imported into Salesforce. This can help improve data quality and accuracy, and reduce data duplication and incompleteness.
Leveraging Salesforce features, such as validation rules, to avoid incomplete and incorrect records (option D). This means using features that allow defining rules and criteria to validate the data that is entered or updated by the users or integrations. This can help prevent invalid or incorrect data from being saved, and trigger actions or alerts to correct or improve the data.


質問 # 15
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