複雑の整理工作も長い時間での待ちもなしで我々のウェブサイトであなたは一番新しく頼もしいSalesforceのPlat-Arch-201試験の資料をもらうことができます。異なるバーションはあなたに違う体験を感じさせます。もちろん、どのバーションのSalesforceのPlat-Arch-201試験の資料でも高品質です。安全的な支払方式PayPalでSalesforce Plat-Arch-201の資料を購入して、直ちにダウンロードして利用できます。
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Salesforce Data Management | 25% | - Describe the implications of LDV on data management - Describe the considerations for data migration - Describe the considerations for data governance - Describe the considerations for data archival |
| Topic 2: Master Data Management | 5% | - Describe the methods for aligning data across systems - Describe the considerations for a Master Data Management strategy |
| Topic 3: Data Modeling/Database Design | 25% | - Describe the considerations when designing a data model for Salesforce - Describe the options and considerations for Large Data Volumes (LDV) - Explain the usage of external objects - Describe the implications of LDV on data modeling |
| Topic 4: Data Migration | 15% | - Describe the considerations for data migration - Describe the implications of data migration on data quality - Describe the tools and best practices for data migration |
| Topic 5: Data Governance | 10% | - Describe the elements of a data governance framework - Describe the considerations for data quality - Describe the considerations for data classification |
| Topic 6: Large Data Volumes | 20% | - Describe the considerations for Large Data Volumes (LDV) - Describe the implications of LDV on data modeling - Describe the features and best practices for LDV |
現状に自己満足して、自分の小さな持ち場を守って少ない給料をもらって解雇されるのを待っている人がいないです。こんな生活はとてもつまらないですから。あなたの人生をよりカラフルにしたいのですか。ここで成功へのショートカットを教えてあげます。即ちSalesforceのPlat-Arch-201認定試験に受かることです。この認証を持っていたら、あなたは、高レベルのホワイトカラーの生活を送ることができます。実力を持っている人になって、他の人に尊敬されることもできます。CertJukenはSalesforceのPlat-Arch-201試験トレーニング資料を提供できます。CertJukenを利用したら、あなたは美しい夢を実現することができます。さあ、ためらわずにCertJukenのSalesforceのPlat-Arch-201試験トレーニング資料をショッピングカートに入れましょう。
質問 # 192
Universal Containers has a requirement to store more than 100 million records in salesforce and needs to create a custom big object to support this business requirement. Which two tools should a data architect use to build custom object?
正解：C、D
解説：
To build a custom big object to support storing more than 100 million records in Salesforce, a data architect should use Metadata API or Big Object in setup. Metadata API is an API that allows developers to create, retrieve, update, or delete metadata components in Salesforce programmatically. Big Object in setup is a user interface that allows admins to create big objects declaratively without writing code. Both tools can be used to define custom big objects and their fields, indexes, and relationships in Salesforce.
質問 # 193
DreamHouse Realty has a Salesforce org that is used to manage Contacts. What are two things an Architect should consider using to maintain data quality in this situation? (Choose two.)
正解：B、D
解説：
Using Salesforce duplicate management and using validation rules on new record create and edit are two things that an architect should consider using to maintain data quality for managing Contacts. Salesforce duplicate management allows the architect to create matching rules and duplicate rules to identify, prevent, or allow duplicate records based on various criteria. Validation rules allow the architect to enforce data quality standards and business logic by displaying error messages when users try to save invalid data. The other options are not relevant or helpful for maintaining data quality
質問 # 194
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?
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 # 195
Universal Containers (UC) uses the following Salesforce products:
- Sales Cloud for customer management.
- Marketing Cloud for marketing.
- Einstein Analytics for business reporting.
UC occasionally gets a list of prospects from third-party source as comma-separated values (CSV) files for marketing purposes. Historically, UC would load contact Lead object in Salesforce and sync to Marketing Cloud to send marketing communications. The number of records in the Lead object has grown over time and has been consuming large amounts of storage in Sales Cloud, UC is looking for recommendations to reduce the storage and advice on how to optimize the marketing Cloud to send marketing communications. The number of records in the Lead object has grown over time and has been consuming large amounts of storage in Sales Cloud, UC is looking for recommendations to reduce the storage and advice on how to optimize the marketing process.
What should a data architect recommend to UC in order to immediately avoid storage issues in the future?
正解：C
解説：
According to the Salesforce documentation, Marketing Cloud is a platform that allows creating and managing marketing campaigns across multiple channels, such as email, mobile, social media, web, etc. Marketing Cloud can integrate with Sales Cloud and other Salesforce products to share data and insights. One of the ways to integrate Marketing Cloud with Sales Cloud is using Marketing Cloud Connect, which allows syncing data between the two platforms using synchronized data sources.
However, if UC occasionally gets a list of prospects from third-party sources as CSV files for marketing purposes, it may not be necessary or efficient to load them into Sales Cloud first and then sync them with Marketing Cloud. This can consume large amounts of storage in Sales Cloud, which has a limit based on the license type. It can also cause data quality issues, such as duplicates or outdated information.
A better option for UC is to load the contacts directly to Marketing Cloud using Import Definition, which allows importing data from external files or databases into Marketing Cloud data extensions. Data extensions are custom tables that store marketing data in Marketing Cloud. This way, UC can avoid storage issues in Sales Cloud and optimize the marketing process by sending marketing communications directly from Marketing Cloud.
To track prospects that are converted to customers, UC can have a reconciliation process that compares the contacts in Marketing Cloud with the accounts or contacts in Sales Cloud. This can be done using SQL queries or API calls to access and compare data from both platforms.
Alternatively, UC can use Marketing Cloud Connect to sync the converted contacts from Sales Cloud to Marketing Cloud using synchronized data sources.
質問 # 196
NTO has implemented salesforce for its sales users. The opportunity management in salesforce is implemented as follows:
1. Sales users enter their opportunities in salesforce for forecasting and reporting purposes.
2. NTO has a product pricing system (PPS) that is used to update opportunity amount field on opportunities on a daily basis.
3. PPS is the trusted source within the NTO for opportunity amount.
4. NTO uses opportunity forecast for its sales planning and management.
Sales users have noticed that their updates to the opportunity amount field are overwritten when PPS updates their opportunities.
How should a data architect address this overriding issue?
正解：C
解説：
Changing the opportunity amount field access to read only for sales users using field level security is the best way to address the overriding issue. This way, the sales users can still view the opportunity amount field but cannot edit it, and PPS can update it as the trusted source
質問 # 197
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