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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Architecture | 20% | - Archiving and data lifecycle management - Governor limits and bulk processing - Performance tuning and optimization - Architecture patterns and design principles |
| Topic 2: Data Integration | 15% | - Sharing rules impact on data integration - ETL tools and data migration strategies - Real-time vs batch integration patterns - API-based integration (REST, SOAP, Bulk API) - Handling locks and parallelism during migration |
| Topic 3: Data Governance | 20% | - Data stewardship roles and responsibilities - Data quality standards and metrics - Data retention and archiving policies - Compliance and regulatory considerations |
| Topic 4: Data Modeling | 25% | - Large Data Volumes (LDV) design considerations - Skinny tables for performance optimization - Indexing strategies - Normalization and denormalization strategies - Big Objects and external objects |
| Topic 5: Master Data Management | 20% | - Identity resolution - Data cleansing techniques - Data duplication and matching rules |
>> Data-Architect Fragenkatalog <<
Die Salesforce Data-Architect Zertifizierungsprüfung ist sehr populär in IT-Industrie. Es spielt eine übergreifende Bedeutung für die Leute, die ihre Arbeitsstelle erhöhen wollen. Und es ist auch die Wahl, die Leute klar sehen können. Außerdem dadurch können Sie Ihre Fähigkeit verbessern und mehr verwendbare Technik beherrschen. Damit können Sie Ihre Arbeit besser fertigen und auch anderen Ihre Fähigkeit zeigen.
84. Frage
Universal Container (US) is replacing a home-grown CRM solution with Salesforce, UC has decided to migrate operational (Open and active) records to Salesforce, while keeping historical records in legacy system, UC would like historical records to be available in Salesforce on an as needed basis.
Which solution should a data architect recommend to meet business requirement?
Antwort: A
Begründung:
According to the Using Mashups article on Salesforce Developers, one of the techniques for deploying large data volumes is to use mashups to display historical records in Salesforce. The article states that "Mashups are a way to display data from an external system within a Salesforce page without copying or synchronizing the data. Mashups use a combination of Visualforce, Apex callouts, and JavaScript code that runs in the browser. Mashups are useful when you want to display large amounts of read-only data that is stored outside of Salesforce." Therefore, a data architect should recommend this solution to meet the business requirement of UC.
85. Frage
UC has a variety of systems across its technology landscape, including SF, legacy enterprise resource planning (ERP) applications and homegrown CRM tools. UC has decided that they would like to consolidate all customer, opportunity and order data into Salesforce as part of its master data management (MDM) strategy.
What are the 3 key steps that a data architect should take when merging data from multiple systems into Salesforce? Choose 3 answers:
Antwort: A,C,D
Begründung:
The three key steps that a data architect should take when merging data from multiple systems into Salesforce are:
Analyze each system's data model and perform gap analysis. This step involves understanding the structure and meaning of the data in each system, identifying the common and unique data elements, and mapping the data fields between the systems. This step also involves assessing the quality and consistency of the data, and identifying any data cleansing or transformation needs.
Utilize an ETL tool to merge, transform, and de-duplicate data. This step involves using an ETL tool to connect to the source systems, extract the data, apply any data transformations or validations, and load the data into Salesforce. This step also involves applying de-duplication rules or algorithms to avoid creating duplicate records in Salesforce.
Work with stakeholders to define record and field survivorship rules. This step involves collaborating with the business users and owners of the data to determine which records and fields should be retained or overwritten in case of conflicts or discrepancies. This step also involves defining the criteria and logic for record and field survivorship, and implementing them in the ETL tool or in Salesforce.
Creating new fields to store additional values from all the systems is not a key step, but rather a possible outcome of the gap analysis. It may not be necessary or desirable to create new fields for every value from every system, as it may result in redundant or irrelevant data. Installing a 3rd party AppExchange tool to handle the merger is not a key step, but rather a possible option for choosing an ETL tool. It may not be the best option depending on the requirements, budget, and preferences of the organization.
86. Frage
Northern Trail Outfitters has these simple requirements for a data export process:
File format should be in CSV.
Process should be scheduled and run once per week.
The expert should be configurable through the Salesforce UI.
Which tool should a data architect leverage to accomplish these requirements?
Antwort: A
87. Frage
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?
Antwort: B
Begründung:
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.
88. Frage
A large retail company has recently chosen SF as its CRM solution. They have the following record counts:
2500000 accounts
25000000 contacts
When doing an initial performance test, the data architect noticed an extremely slow response for reports and list views.
What should a data architect do to solve the performance issue?
Antwort: B
89. Frage
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