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| Section | Weight | Objectives |
|---|---|---|
| Master Data Management | 20% | - Data duplication and matching rules - Data cleansing techniques - Identity resolution |
| Data Modeling | 25% | - Large Data Volumes (LDV) design considerations - Normalization and denormalization strategies - Big Objects and external objects - Indexing strategies - Skinny tables for performance optimization |
| Data Integration | 15% | - Real-time vs batch integration patterns - Sharing rules impact on data integration - ETL tools and data migration strategies - Handling locks and parallelism during migration - API-based integration (REST, SOAP, Bulk API) |
| Data Governance | 20% | - Compliance and regulatory considerations - Data stewardship roles and responsibilities - Data retention and archiving policies - Data quality standards and metrics |
| Data Architecture | 20% | - Archiving and data lifecycle management - Performance tuning and optimization - Architecture patterns and design principles - Governor limits and bulk processing |
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NEW QUESTION # 194
Northern Trail Outfitters needs to implement an archive solution for Salesforce dat a. This archive solution needs to help NTO do the following:
1. Remove outdated Information not required on a day-to-day basis.
2. Improve Salesforce performance.
Which solution should be used to meet these requirements?
Answer: C
Explanation:
Identifying a location to store archived data and using scheduled batch jobs to migrate and purge the aged data on a nightly basis can be a way to meet the requirements for an archive solution. The article provides a use case of how to use Heroku Connect, Postgres, and Salesforce Connect to archive old data, free up space in the org, and still retain the option to unarchive the data if needed. The article also explains how this solution can improve Salesforce performance and meet data retention policies.
NEW QUESTION # 195
Cloud Kicks is launching a Partner Community, which will allow users to register shipment requests that are then processed by Cloud Kicks employees. Shipment requests contain header information, and then a list of no more than 5 items being shipped.
First, Cloud Kicks will introduce its community to 6,000 customers in North America, and then to 24,000 customers worldwide within the next two years. Cloud Kicks expects 12 shipment requests per week per customer, on average, and wants customers to be able to view up to three years of shipment requests and use Salesforce reports.
What is the recommended solution for the Cloud Kicks Data Architect to address the requirements?
Answer: D
Explanation:
The recommended solution for the Cloud Kicks Data Architect to address the requirements is to create a custom object to track shipment requests and a child custom object to track shipment items. Implement an archiving process that moves data off-platform after three years. This solution would allow Cloud Kicks to store and manage their shipment data on Salesforce, and use Salesforce reports to analyze it. However, since Cloud Kicks expects a large volume of data over time, they should implement an archiving process that moves data off-platform after three years to avoid hitting the Org data storage limit and maintain optimal performance3. External objects are not a good option for this scenario, because they are stored off-platform in an external system, such as Heroku's Postgres database, and they have limited functionality and performance compared to custom objects
NEW QUESTION # 196
NTO has a loyalty program to reward repeat customers. The following conditions exists:
1.Reward levels are earned based on the amount spent during the previous 12 months.
2.The program will track every item a customer has bought and grant them points for discount.
3.The program generates 100 million records each month.
NTO customer support would like to see a summary of a customer's recent transaction and reward level(s) they have attained.
Which solution should the data architect use to provide the information within the salesforce for the customer support agents?
Answer: B
Explanation:
According to the Get Started with Big Objects unit on Trailhead, one of the use cases for custom big objects is to store and manage loyalty program data for customers. The unit states that "From loyalty programs to transactions, order, and billing information, use a custom big object to keep track of every detail." Therefore, a custom big object can be used to capture the reward program data and display it on the contact record.
Additionally, according to the Big Objects Implementation Guide, big objects can handle massive amounts of data (up to billions of records) and can be updated nightly from external systems using Bulk API or batch Apex. Therefore, a custom big object can meet the requirements of NTO's loyalty program scenario.
NEW QUESTION # 197
Northern Trail Outfitters is concerned because some of its data is sensitive and needs to be identified for access.
What should be used to provide ways to filter and identify the sensitive data?
Answer: D
Explanation:
According to the official Salesforce guide1, data classification metadata is a feature that allows administrators to classify data fields based on their sensitivity level, such as confidential, restricted, or general. Data classification metadata can be used to filter and identify sensitive data fields and apply appropriate security measures, such as encryption, masking, or auditing. Option D is the correct answer because it suggests using data classification metadata to provide ways to filter and identify sensitive data. Option A is incorrect because data grouping metadata is not a feature in Salesforce. Option B is incorrect because field-level security is a feature that controls the visibility and editability of fields based on user profiles or permission sets, but it does not provide ways to filter and identify sensitive data. Option C is incorrect because creating a custom checkbox denoting sensitive data is not a scalable or reliable solution, as it requires manual maintenance and does not enforce any security measures.
NEW QUESTION # 198
Universal Containers (UC) requires 2 years of customer related cases to be available on SF for operational reporting. Any cases older than 2 years and upto 7 years need to be available on demand to the Service agents.
UC creates 5 million cases per yr.
Which 2 data archiving strategies should a data architect recommend? Choose 2 options:
Answer: C,D
Explanation:
The best data archiving strategies for UC are to use Big objects and Heroku with external objects. Big objects allow storing large amounts of data on the Salesforce platform without affecting performance or storage limits. They also support point-and-click tools, triggers, and Apex code. Heroku is a cloud platform that can host external databases and integrate with Salesforce using external objects. External objects enable on- demand access to external data sources via standard Salesforce APIs and user interfaces. Using bulk API to hard delete cases from Salesforce will free up storage space and improve performance.
NEW QUESTION # 199
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