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| Section | Objectives |
|---|---|
| Salesforce Data Model and Platform Capabilities | - Standard and custom objects - Reporting and analytics considerations - Relationships and schema design |
| Data Management | - Data governance principles - Master data management (MDM) concepts - Data quality management |
| Data Architecture and Design | - Data modeling best practices in Salesforce - Conceptual and logical data modeling - Handling large data volume and scalability considerations |
| Data Integration | - ETL vs ELT strategies - Integration patterns in Salesforce - API-based integration approaches |
| Data Migration | - Data migration strategies and planning - Data cleansing and transformation |
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If you have prepared well, tried all the Salesforce Certified Platform Data Architect Exams, and understood each concept clearly, there is minimal or no chance of failure. Desktop Practice exam software and web-based Salesforce Certified Platform Data Architect (Plat-Arch-201) practice test are available at ITexamReview. These Salesforce Certified Platform Data Architect (Plat-Arch-201) practice test questions are customizable and give real Salesforce Certified Platform Data Architect (Plat-Arch-201) exam experience. Windows computers support desktop software. The web-based Plat-Arch-201 practice exam is supported by all browsers and operating systems.
NEW QUESTION # 220
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 answer
Answer: A,C,D
Explanation:
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.
NEW QUESTION # 221
Universal Containers (UC) has implemented Sales Cloud and it has been noticed that Sales reps are not entering enough data to run insightful reports and dashboards. UC executives would like to monitor and measure data quality metrics. What solution addresses this requirement?
Answer: B
Explanation:
Using third-party AppExchange tools to monitor and measure data quality can address the requirement of UC executives by providing features such as data cleansing, deduplication, validation, enrichment, and scoring. These tools can help improve the accuracy, completeness, and consistency of the data entered by sales reps .
NEW QUESTION # 222
Get Cloudy Consulting is migrating their legacy system's users and data to Salesforce. They will be creating 15,000 users, 1.5 million Account records, and 15 million Invoice records. The visibility of these records is controlled by a 50 owner and criteria-based sharing rules. Get Cloudy Consulting needs to minimize data loading time during this migration to a new organization.
Which two approaches will accomplish this goal? (Choose two.)
Answer: B,D
Explanation:
Creating the users, uploading all data, and then deploying the sharing rules will reduce the number of sharing recalculations that occur during the data load. Deferring sharing calculations until the data has finished uploading will also improve the performance by postponing the sharing rule evaluation. These are the recommended best practices for loading large data sets into Salesforce
NEW QUESTION # 223
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?
Answer: D
Explanation:
According to the exam guide, one of the objectives is to "describe the use cases and considerations for deferring sharing calculations". 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 later.
NEW QUESTION # 224
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?
Answer: C
Explanation:
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.
NEW QUESTION # 225
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