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| Section | Weight | Objectives |
|---|---|---|
| Large Data Volumes | 20% | - Describe the features and best practices for LDV - Describe the considerations for Large Data Volumes (LDV) - Describe the implications of LDV on data modeling |
| Salesforce Data Management | 25% | - Describe the considerations for data governance - Describe the considerations for data migration - Describe the implications of LDV on data management - Describe the considerations for data archival |
| Data Migration | 15% | - Describe the considerations for data migration - Describe the tools and best practices for data migration - Describe the implications of data migration on data quality |
| Master Data Management | 5% | - Describe the methods for aligning data across systems - Describe the considerations for a Master Data Management strategy |
| Data Modeling/Database Design | 25% | - Describe the considerations when designing a data model for Salesforce - Describe the implications of LDV on data modeling - Explain the usage of external objects - Describe the options and considerations for Large Data Volumes (LDV) |
| Data Governance | 10% | - Describe the considerations for data classification - Describe the elements of a data governance framework - Describe the considerations for data quality |
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NEW QUESTION # 186
UC is having issues using Informatica Cloud Louder to export +10MOrder records. Each Order record has 10 Order Line Items. What two steps can you take to help correct this? Choose two answers.
Answer: A,D
Explanation:
Exporting in multiple batches and using PK Chunking are two steps that can help correct the issues with exporting large volumes of Order records using Informatica Cloud Loader. Exporting in multiple batches can reduce the load on the system and avoid timeouts or errors. Using PK Chunking can split a large data set into smaller chunks based on the record IDs and enable parallel processing of each chunk.
NEW QUESTION # 187
Universal Containers (UC) has multi-level account hierarchies that represent departments within their major Accounts. Users are creating duplicate Contacts across multiple departments. UC wants to clean the data so as to have a single Contact across departments. What two solutions should UC implement to cleanse their data? Choose 2 answer
Answer: B,C
Explanation:
Making use of a third-party tool to help merge duplicate Contacts across Accounts and using Data.com to standardize Contact address information to help identify duplicates are two solutions that UC should implement to cleanse their data and have a single Contact across departments. A third-party tool, such as an app from the AppExchange, can provide advanced features and capabilities for finding and merging duplicate Contacts across different Accounts, based on various criteria and rules. Data.com can provide address verification and standardization services that can enhance the quality and consistency of Contact address information and make it easier to identify duplicates. The other options are not feasible or effective for cleansing the data, as they would either not work across different Accounts, not address the root cause of duplication, or not provide sufficient functionality for merging duplicates
NEW QUESTION # 188
Universal Containers (UC) loads bulk leads and campaigns from third-party lead aggregators on a weekly and monthly basis. The expected lead record volume is 500K records per week, and the expected campaign records volume is 10K campaigns per week. After the upload, Lead records are shared with various sales agents via sharing rules and added as Campaign members via Apex triggers on Lead creation. UC agents work on leads for 6 months, but want to keep the records in the system for at least 1 year for reference. Compliance requires them to be stored for a minimum of 3 years. After that, data can be deleted. What statement is true with respect to a data archiving strategy for UC?
Answer: C
Explanation:
Leveraging a "tier"-based approach to classify the record storage need is a true statement with respect to a data archiving strategy for UC. This approach involves defining different tiers of data based on their usage, value, and retention policies, and then applying appropriate storage and archiving solutions for each tier.
NEW QUESTION # 189
How can an architect find information about who is creating, changing, or deleting certain fields within the past two months?
Answer: D
Explanation:
The setup audit trail tracks changes made in your org's setup area for the past 180 days. You can export the setup audit trail and find the fields in question by filtering by action type, user, or date.
NEW QUESTION # 190
US has released a new disaster recovery (DR)policy that states that cloud solutions need a business continuity plan in place separate from the cloud providers built in data recovery solution.
Which solution should a data architect use to comply with the DR policy?
Answer: D
Explanation:
The best solution to comply with the DR policy is to leverage a 3rd party tool that extract Salesforce data/metadata and stores the information in an external protected system. This solution can help create a backup of Salesforce data and metadata in case of a disaster or data loss event. It can also help restore data from the backup system to Salesforce if needed. There are various 3rd party tools available in the AppExchange or online that offer data backup and recovery services for Salesforce. Leverage Salesforce weekly exports and store data in flat files on a protected system is not a good solution because it does not include metadata backup and it does not allow granular or automated data recovery. Utilize an ETL tool to migrate data to an on- premise archive solution is not a good solution because it does not include metadata backup and it may require complex data transformations and synchronizations. Write a custom batch job to extract data changes nightly and store in an external protected system is not a good solution because it does not include metadata backup and it may have performance or reliability issues.
NEW QUESTION # 191
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