ちなみに、CertShiken Data-Architectの一部をクラウドストレージからダウンロードできます：https://drive.google.com/open?id=1qn-Rykuh9LQR1C7VsRodRPNAXoC5gJJL
社会に入った後の私達は最もの責任があって、学習の時間は少なくなりました。IT領域により良く発展したいなら、Salesforce Data-Architectのような試験認定資格を取得するのは重要なことです。周知のようにSalesforce Data-Architectのような試験認定資格を手に入れると、会社の規則に沿う奨励があります。それで、速く我々CertShikenのSalesforce Data-Architect試験問題集を入手しましょう。
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Architecture | 20% | - Performance tuning and optimization - Governor limits and bulk processing - Archiving and data lifecycle management - Architecture patterns and design principles |
| Topic 2: Data Modeling | 25% | - Large Data Volumes (LDV) design considerations - Indexing strategies - Normalization and denormalization strategies - Big Objects and external objects - Skinny tables for performance optimization |
| Topic 3: Data Integration | 15% | - Sharing rules impact on data integration - Real-time vs batch integration patterns - Handling locks and parallelism during migration - API-based integration (REST, SOAP, Bulk API) - ETL tools and data migration strategies |
| Topic 4: Master Data Management | 20% | - Data cleansing techniques - Identity resolution - Data duplication and matching rules |
| Topic 5: Data Governance | 20% | - Data stewardship roles and responsibilities - Compliance and regulatory considerations - Data retention and archiving policies - Data quality standards and metrics |
Data-Architect試験シミュレーションは、競争力を向上させる優れたツールです。学習資料を使用した後、Salesforce認定をより早く取得できます。この認定により、より多くの機会が与えられます。 Data-Architect準備の質問の助けを借りて、あなたの周りの同僚と比較して、より効率的な仕事のパフォーマンスを得ることができます。 Data-Architect学習教材には、次の機能があるため、非常に多くのメリットがあります。コーヒーを1杯使ってData-Architectトレーニングエンジンについて学習していただければ幸いです。おそらくこれがあなたの変化の始まりです。
質問 # 97
Universal Container is using Salesforce for Opportunity management and enterprise resource planning (ERP) for order management. Sales reps do not have access to the ERP and have no visibility into order status.
What solution a data architect recommend to give the sales team visibility into order status?
正解：C
質問 # 98
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.
Developing custom APIs to poll the hub org for change data and push into the spoke orgs (option B) is not a good solution, as it can be complex, costly, and difficult to maintain. It may also not be able to handle large volumes of data or complex transformations efficiently. Developing custom APIs to poll the spoke orgs for change data and push into the hub org (option C) is also not a good solution, as it can have the same drawbacks as option B. It may also not be able to handle conflicts or errors effectively. Using a backup and archive solution that extracts and restores data across orgs (option D) is also not a good solution, as it can incur additional costs and dependencies. It may also not be able to handle real-time or near-real-time data orchestration requirements.
質問 # 99
NTO need to extract 50 million records from a custom object everyday from its Salesforce org. NTO is facing query timeout issues while extracting these records.
What should a data architect recommend in order to get around the time out issue?
正解：A
解説：
The best solution to extract 50 million records from a custom object everyday from Salesforce org without facing query timeout issues is to use an ETL tool for extraction of records. ETL stands for extract, transform, and load, and it refers to a process of moving data from one system to another. An ETL tool is a software application that can connect to various data sources, perform data transformations, and load data into a target destination. ETL tools can handle large volumes of data efficiently and reliably, and they often provide features such as scheduling, monitoring, error handling, and logging 5 . Using a custom auto number and formula field and use that to chunk records while extracting data is a possible workaround, but it requires creating additional fields and writing complex queries. The REST API can extract data as it automatically chunks records by 200, but it has some limitations, such as a maximum of 50 million records per query job 6
. Asking SF support to increase the query timeout value is not feasible because query timeout values are not configurable
質問 # 100
DreamHouse Realty has a data model as shown in the image. The Project object has a private sharing model, and it has Roll-Up summary fields to calculate the number of resources assigned to the project, total hours for the project, and the number of work items associated to the project.
There will be a large amount of time entry records to be loaded regularly from an external system into Salesforce.
What should the Architect consider in this situation?
正解：A
解説：
According to the exam guide, one of the objectives is to "describe the use cases and considerations for deferring sharing calculations"1. This implies that option A is the correct way to load large amounts of data into Salesforce without affecting performance and data integrity. Deferring sharing calculations allows the data to be loaded first and then the sharing rules to be applied later2. Option B is not correct because workflows are not recommended for calculating summary values, as they can cause performance issues and data skew3. Option C is not correct because triggers are also not recommended for calculating summary values, as they can cause governor limit errors and data inconsistency. Option D is not correct because external IDs are used to link records from different systems, not to improve data loading performance.
質問 # 101
A company wants to document the data architecture of a Salesforce organization.
What are two valid metadata types that should be included? (Choose two.)
正解：B、C
解説：
Option A is correct because RecordType is a valid metadata type that should be included in documenting the data architecture of a Salesforce organization 1 . RecordType defines different business processes, picklist values, and page layouts for different users 2 . Option C is correct because CustomField is another valid metadata type that should be included in documenting the data architecture of a Salesforce organization 1
. CustomField defines custom attributes for standard or custom objects 3 . Option B is not correct because Document is not a valid metadata type, but a standard object that stores documents in folders 4 . Option D is not correct because SecuritySettings is not a valid metadata type, but a setup menu that allows administrators to configure various security features such as password policies, network access, session settings, etc.
質問 # 102
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時代の発展に伴い、人間的な文明が発展し、CertShikenも発展しています。CertShikenは君の早くSalesforceのData-Architect認定試験に合格するために、きみのもっと輝い未来のために、君の他人に羨ましいほど給料のために、ずっと努力しています。長年の努力を通じて、CertShikenのSalesforceのData-Architect認定試験の合格率が１００パーセントになっていました。CertShikenを選ぶなら、成功を選ぶのに等しいです。
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