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| Section | Objectives |
|---|---|
| Topic 1: Data Migration | - Data migration strategies and planning - Data cleansing and transformation |
| Topic 2: Salesforce Data Model and Platform Capabilities | - Standard and custom objects - Reporting and analytics considerations - Relationships and schema design |
| Topic 3: Data Management | - Data governance principles - Data quality management - Master data management (MDM) concepts |
| Topic 4: Data Architecture and Design | - Handling large data volume and scalability considerations - Conceptual and logical data modeling - Data modeling best practices in Salesforce |
| Topic 5: Data Integration | - ETL vs ELT strategies - API-based integration approaches - Integration patterns in Salesforce |
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NEW QUESTION # 71
During the implementation of Salesforce, a customer has the following requirements for Sales Orders:
1. Sales Order information needs to be shown to users in Salesforce.
2. Sales Orders are maintained in the on-premises enterprise resource planning (ERP).
3. Sales Order information has more than 150 million records.
4. Sales Orders will not be updated in Salesforce.
What should a data architect recommend for maintaining Sales Orders in salesforce?
Answer: D
Explanation:
Using external objects to maintain Sales Order in Salesforce is the best recommendation for maintaining Sales Orders in Salesforce, as it allows users to access large volumes of data stored outside Salesforce without copying or synchronizing it. Using custom objects, custom big objects, or standard order object may not be feasible or optimal for storing more than 150 million records that will not be updated in Salesforce.
NEW QUESTION # 72
Universal Containers has more than 10 million records in the Order_c object. The query has timed out when running a bulk query. What should be considered to resolve query timeout?
Answer: B
Explanation:
PK Chunking can resolve query timeout when running a bulk query on an object with more than
10 million records. PK Chunking is a feature of the Bulk API that splits a query into multiple batches based on the record IDs (primary keys) of the queried object. This can improve the query performance and avoid timeouts by reducing the number of records processed in each batch.
NEW QUESTION # 73
Northern trail Outfitters (NTO) runs its entire out of an enterprise data warehouse (EDW), NTD's sales team starting to use Salesforce after a recent implementation, but currently lacks data required to advanced and opportunity to the next stage.
NTO's management has research Salesforce Connect and would like to use It to virtualize and report on data from the EDW within Salesforce. NTO will be running thousands of reports per day across 10 to 15 external objects.
What should a data architect consider before implementing Salesforce Connect for reporting?
Answer: C
Explanation:
According to the Salesforce Connect Reporting blog post, one of the considerations for using Salesforce Connect for reporting is the OData callout limits per day. The blog post states that
"Salesforce Connect has a limit of 100,000 callouts per day. This limit is shared across all external data sources in your org. If you exceed this limit, you will receive an error message and no more callouts will be allowed until the next day." Therefore, a data architect should consider this limit before implementing Salesforce Connect for reporting.
NEW QUESTION # 74
A large insurance provider is looking to implement Salesforce. The following exist.
1. Multiple channel for lead acquisition
2. Duplication leads across channels
3. Poor customer experience and higher costs
On analysis, it found that there are duplicate leads that are resulting to mitigate the issues?
Answer: A,B,D
Explanation:
According to the Salesforce documentation, duplicate leads are leads that have the same or similar information as other leads in Salesforce. Duplicate leads can cause poor customer experience, higher costs, and inaccurate reporting. To mitigate the issues caused by duplicate leads, some of the recommended practices are:
Standardize lead information across all channels (option B). This means using consistent formats, values, and fields for capturing lead data from different sources, such as web forms, email campaigns, or third-party vendors. This can help reduce data quality issues and make it easier to identify and prevent duplicate leads.
Implement a third-party solution to clean and enrich lead data (option D). This means using an external service or tool that can validate, correct, update, and enhance lead data before or after importing it into Salesforce. This can help improve data quality and accuracy, and reduce duplicate leads.
Implement a de-duplication strategy to prevent duplicate leads (option E). This means using Salesforce features or custom solutions that can detect and block duplicate leads from being created or imported into Salesforce. For example, using Data.com Duplicate Management, which allows defining matching rules and duplicate rules for leads and other objects.
NEW QUESTION # 75
Universal Containers (UC) is concerned about the accuracy of their Customer information in Salesforce. They have recently created an enterprise-wide trusted source MDM for Customer data which they have certified to be accurate. UC has over 20 million unique customer records in the trusted source and Salesforce. What should an Architect recommend to ensure the data in Salesforce is identical to the MDM?
Answer: C
Explanation:
Using an AppExchange package for Data Quality is a good way to match Salesforce data against a trusted source, such as an MDM system. You can use tools like Cloudingo, DupeCatcher, or DemandTools to identify and merge duplicate records, standardize data formats, and enrich data with external sources
NEW QUESTION # 76
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