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| Section | Objectives |
|---|---|
| Topic 1: Data Management | - Master data management (MDM) concepts - Data quality management - Data governance principles |
| Topic 2: Salesforce Data Model and Platform Capabilities | - Reporting and analytics considerations - Standard and custom objects - Relationships and schema design |
| Topic 3: Data Migration | - Data migration strategies and planning - Data cleansing and transformation |
| Topic 4: Data Integration | - Integration patterns in Salesforce - ETL vs ELT strategies - API-based integration approaches |
| Topic 5: Data Architecture and Design | - Data modeling best practices in Salesforce - Handling large data volume and scalability considerations - Conceptual and logical data modeling |
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NEW QUESTION # 44
UC has the following system:
- Billing system.
- Customer support system.
- CRM system.
US has been having trouble with business intelligence across the different systems. Recently US implemented a master data management (MDM) solution that will be the system of truth for the customer records.
Which MDM data element is needed to allow reporting across these systems?
Answer: B
Explanation:
The correct answer is A, global unique customer number. A global unique customer number is a data element that can uniquely identify each customer across different systems. It can be used as a key to link customer records from different sources and enable reporting across these systems.
Email address, phone number, and full name are not reliable or consistent identifiers for customers, as they can change over time or be shared by multiple customers.
NEW QUESTION # 45
What is the main purpose of Big Objects?
Answer: D
Explanation:
Big Objects handle billions of records.
NEW QUESTION # 46
Universal Containers has a custom object with millions of rows of data. When executing SOQL queries, which three options prevent a query from being selective? (Choose three.)
Answer: A,C,E
Explanation:
Using leading % wildcards, performing large loads and deletions, and using NOT and != operators are three options that prevent a query from being selective. These options can cause the query to scan a large number of records or indexes, which can negatively impact the performance and scalability of the query. Using a custom index on a deterministic formula field, on the other hand, can improve the query selectivity by allowing the query to use the index instead of scanning all the records6.
NEW QUESTION # 47
Universal Containers (CU) is in the process of implementing an enterprise data warehouse (EDW). UC needs to extract 100 million records from Salesforce for migration to the EDW. What data extraction strategy should a data architect use for maximum performance?
Answer: C
Explanation:
According to the Salesforce documentation, extracting large amounts of data from Salesforce can be challenging and time-consuming, as it can encounter performance issues, API limits, timeouts, etc. To extract 100 million records from Salesforce for migration to an enterprise data warehouse (EDW), a data extraction strategy that can provide maximum performance is:
Utilize PK Chunking with the Bulk API (option C). This means using a feature that allows splitting a large query into smaller batches based on the record IDs (primary keys) of the queried object.
This can improve performance and avoid timeouts by processing each batch asynchronously and in parallel using the Bulk API.
NEW QUESTION # 48
In their legacy system. Universal Containers has a monthly accounts receivable report that compiles data from Accounts, Contacts, Opportunities, Orders. and Order Line Items. What difficulty will an architect run into when implementing this in Salesforce?
Answer: A
Explanation:
Salesforce allows up to four objects in a single report type. This means that if an architect wants to create a report that compiles data from Accounts, Contacts, Opportunities, Orders, and Order Line Items, they will run into a difficulty because that would require five objects in a single report type. To overcome this limitation, the architect can either create two separate report types and join them in a joined report, or use an external reporting tool that can access data from multiple objects.
NEW QUESTION # 49
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