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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Modeling/Database Design | 25% | - Describe the options and considerations for Large Data Volumes (LDV) - Describe the considerations when designing a data model for Salesforce - Describe the implications of LDV on data modeling - Explain the usage of external objects |
| Topic 2: Data Governance | 10% | - Describe the considerations for data classification - Describe the elements of a data governance framework - Describe the considerations for data quality |
| Topic 3: Master Data Management | 5% | - Describe the considerations for a Master Data Management strategy - Describe the methods for aligning data across systems |
| Topic 4: Data Migration | 15% | - Describe the implications of data migration on data quality - Describe the considerations for data migration - Describe the tools and best practices for data migration |
| Topic 5: Salesforce Data Management | 25% | - Describe the considerations for data governance - Describe the considerations for data archival - Describe the considerations for data migration - Describe the implications of LDV on data management |
| Topic 6: Large Data Volumes | 20% | - Describe the features and best practices for LDV - Describe the implications of LDV on data modeling - Describe the considerations for Large Data Volumes (LDV) |
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NEW QUESTION # 228
Universal Containers (UC) is building a Service Cloud call center application and has a multisystem support solution. UC would like or ensure that all systems have access to the same customer information. What solution should a data architect recommend?
Answer: A
Explanation:
A master data management (MDM) strategy for customer data can help UC ensure that all systems have access to the same customer information, without loading or duplicating data in all systems. An MDM strategy can also help UC avoid data conflicts and inconsistencies that may arise from having multiple systems as owners of data.
NEW QUESTION # 229
Northern Trail Outfitters (NTO) has multiple Salesforce orgs based on regions. Users need read- only access to customers across all Salesforce orgs. Which feature in Salesforce can be used to provide access to customer records across all NTO orgs?
Answer: C
Explanation:
Salesforce Connect is a feature that allows users to access data from external sources and multiple Salesforce orgs, using either clicks or code. Salesforce Connect can provide read-only access to customer records across all NTO orgs, without replicating or storing the data in Salesforce.
NEW QUESTION # 230
A Customer is migrating 10 million order and 30 million order lines into Salesforce using Bulk API.
The Engineer is experiencing time-out errors or long delays querying parents order IDs in Salesforce before importing related order line items. What is the recommended solution?
Answer: B
Explanation:
Leverage an External ID from source system orders to import related order lines. This is the recommended solution because it allows you to use the upsert operation to match records based on the External ID field, which is indexed and unique. This avoids the need to query the parent order IDs in Salesforce before importing the order line items, which can cause time-out errors or long delays.
NEW QUESTION # 231
Get Cloudy Consulting needs to evaluate the completeness and consistency of contact information in Salesforce. Their sales reps often have incomplete information about their accounts and contacts. Additionally, they are not able to interpret the information in a consistent manner. Get Cloudy Consulting has identified certain ""key"" fields which are important to their sales reps. What are two actions Get Cloudy Consulting can take to review their data for completeness and consistency? (Choose two.)
Answer: C,D
Explanation:
Running a report that shows the last time the key fields were updated can help Get Cloudy Consulting identify stale or outdated data and prioritize data cleansing activities. Running a report that shows the percentage of blanks for the important fields can help Get Cloudy Consulting measure the completeness of their data and identify gaps or missing value
NEW QUESTION # 232
DreamHouse Realty has a legacy system that captures Branch Offices and Transactions.
DreamHouse Realty has 15 Branch Offices. Transactions can relate to any Branch Office.
DreamHouse Realty has created hundreds of thousands of Transactions per year. A Data Architect needs to denormalize this data model into a single Transaction object with a Branch Office picklist. What are two important considerations for the Data Architect in this scenario?
(Choose two.)
Answer: A,D
Explanation:
The Data Architect should consider the limitations on Org data storage and the Bulk API limitations on picklist fields when denormalizing the data model into a single Transaction object with a Branch Office picklist. The Org data storage limit is the total amount of data that can be stored in a Salesforce Org, and it depends on the edition and license type of the Org. The Bulk API limit on picklist fields is the maximum number of values that can be imported or exported using the Bulk API, and it is 1,000 values per picklist field. These limitations could affect the performance and scalability of the data model, and the Data Architect should plan accordingly.
NEW QUESTION # 233
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