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| Section | Objectives |
|---|---|
| Data Migration | - Data migration strategies and planning - Data cleansing and transformation |
| Salesforce Data Model and Platform Capabilities | - Standard and custom objects - Reporting and analytics considerations - Relationships and schema design |
| Data Integration | - Integration patterns in Salesforce - ETL vs ELT strategies - API-based integration approaches |
| Data Management | - Master data management (MDM) concepts - Data quality management - Data governance principles |
| Data Architecture and Design | - Handling large data volume and scalability considerations - Data modeling best practices in Salesforce - Conceptual and logical data modeling |
Getting the Salesforce Certified Platform Data Architect (Plat-Arch-201) certification is the way to go if you're planning to get into Salesforce or want to start earning money quickly. Success in the Salesforce Certified Platform Data Architect (Plat-Arch-201) exam of this credential plays an essential role in the validation of your skills so that you can crack an interview or get a promotion in an Salesforce company. Many people are attempting the Salesforce Plat-Arch-201 test nowadays because its importance is growing rapidly.
NEW QUESTION # 217
Universal Containers (UC) is implementing a formal, cross -business -unit data governance program As part of the program, UC will implement a team to make decisions on enterprise -wide data governance. Which two roles are appropriate as members of this team? Choose 2 answer
Answer: B,C
Explanation:
Analytics/BI Owners and Data Domain Stewards are appropriate roles as members of a team that makes decisions on enterprise-wide data governance. Analytics/BI Owners are responsible for defining the business requirements and metrics for data analysis and reporting, and Data Domain Stewards are responsible for defining and enforcing the data quality standards and rules for specific data domains. Salesforce Administrators and Operational Data Users are not suitable roles for this team, as they are more focused on the operational aspects of data management, such as configuration, maintenance, and usage.
NEW QUESTION # 218
An architect is planning on having different batches to load one million Opportunities into Salesforce using the Bulk API in parallel mode. What should be considered when loading the Opportunity records?
Answer: C
Explanation:
Ordering batches by Auto-number field will ensure that the records are processed in a sequential order and avoid any locking issues that might occur when loading related records in parallel mode. Creating indexes, grouping batches by AccountId, or sorting batches by Name field values are not necessary or beneficial for loading Opportunity records using the Bulk API.
NEW QUESTION # 219
Which API is best for loading millions of records asynchronously?
Answer: D
Explanation:
Bulk API is optimized for large-scale data loads.
NEW QUESTION # 220
Universal Containers (UC) is a major supplier of office supplies. Some products are produced by UC and some by other manufacturers. Recently, a number of customers have complained that product descriptions on the invoices do not match the descriptions in the online catalog and on some of the order confirmations (e.g., "ballpoint pen" in the catalog and "pen" on the invoice, and item color labels are inconsistent: "what vs. "White" or "blk" vs. "Black"). All product data is consolidated in the company data warehouse and pushed to Salesforce to generate quotes and invoices. The online catalog and webshop is a Salesforce Customer Community solution. What is a correct technique UC should use to solve the data inconsistency?
Answer: D
Explanation:
A correct technique UC should use to solve the data inconsistency is to define a data taxonomy for product data and apply the taxonomy to the product data in the data warehouse. A data taxonomy is a hierarchical classification of data entities and attributes that defines their meaning, format, and relationships. A data taxonomy can help ensure consistency, accuracy, and completeness of product data across different systems and channels
NEW QUESTION # 221
Cloud Kicks stores Invoice records in a custom object. Invoice records are being sent to the Accounting department with missing States and incorrectly formatted Postal Codes. Which two actions should Cloud Kicks take to improve data quality? (Choose two.)
Answer: A,D
Explanation:
Utilizing a Validation Rule with a REGEX operator on Postal Code and utilizing a Validation Rule with a CONTAINS operator on address fields are two actions that Cloud Kicks should take to improve data quality for their Invoice records. A Validation Rule with a REGEX operator can check if the Postal Code field matches a specific pattern or format, such as a five-digit number or a combination of letters and numbers. A Validation Rule with a CONTAINS operator can check if the address fields contain certain values, such as valid state abbreviations or country names.
These Validation Rules can prevent users from saving invalid or incomplete data and display error messages to guide them to correct the data. The other options are not effective or recommended for improving data quality, as they would either require additional customization, not enforce data standards, or not address the specific issues of missing states and incorrectly formatted postal codes
NEW QUESTION # 222
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