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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Integration | 15% | - API-based integration (REST, SOAP, Bulk API) - Handling locks and parallelism during migration - Sharing rules impact on data integration - ETL tools and data migration strategies - Real-time vs batch integration patterns |
| Topic 2: Data Modeling | 25% | - Indexing strategies - Normalization and denormalization strategies - Large Data Volumes (LDV) design considerations - Big Objects and external objects - Skinny tables for performance optimization |
| Topic 3: Master Data Management | 20% | - Data cleansing techniques - Data duplication and matching rules - Identity resolution |
| Topic 4: Data Governance | 20% | - Data stewardship roles and responsibilities - Data retention and archiving policies - Data quality standards and metrics - Compliance and regulatory considerations |
| Topic 5: Data Architecture | 20% | - Archiving and data lifecycle management - Governor limits and bulk processing - Performance tuning and optimization - Architecture patterns and design principles |
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NEW QUESTION # 56
A consumer products company has decided to use Salesforce for its contact center. The contact center agents need access to the following information in Service Console when a customer contacts them:
1. Customer browsing activity on its website stored on its on premise system
2. Customer interactions with sales associates at its retail stores maintained in Salesforce
3. Contact center interactions maintained in Salesforce
4. Email campaign activity to customer from its marketing systems.
What should a data architect do to fulfill these requirements with minimum development effort in Salesforce?
Answer: C
NEW QUESTION # 57
Universal Containers (UC) has a complex system landscape and is implementing a data governance program for the first time Which two first steps would be appropriate for UC to initiate an assessment of data architecture? Choose 2 answers
Answer: B,D
NEW QUESTION # 58
Universal Containers (UC) owns several Salesforce orgs across a variety of business units. UC management has declared that it needs the ability to report on Accounts and Opportunities from each org in one place. Once the data is brought together into a global view, management would like to use advanced Al-driven analytics on the dataset.
Which tool should a data architect recommend to accomplish this reporting requirement?
Answer: A
Explanation:
According to this article, Einstein Analytics for multi-org can help UC to report on accounts and opportunities from each org in one place. It can also provide advanced AI-driven analytics on the dataset using Einstein Discovery.
NEW QUESTION # 59
A casino is implementing salesforce and is planning to build a customer 360 view for a customer who visits its resorts. The casino currently maintained the following systems that records customer activity:
1. Point of sales system: All purchases for a customer.
2. Salesforce: All customer service activity and sales activity for a customer.
3. Mobile app: All bookings, preferences and browser activity for a customer.
4. Marketing: All email, SMS and social campaigns for a customer.
Customer service agents using salesforce would like to view the activities from all system to provide supports to customers. The information has to be current and real time.
What strategy should the data architect implement to satisfy this requirement?
Answer: D
Explanation:
Exploring external data sources in Salesforce to build 360 view of customer is the best strategy to satisfy the requirement, as it allows real-time access to data from other systems without storing it in Salesforce3. Using a customer data mart may not provide real-time information or may require additional integration efforts. Migrating customer activities from all 4 systems into Salesforce may exceed the storage limits or cause data quality issues. Periodically uploading summary information in Salesforce may not provide current or detailed information.
NEW QUESTION # 60
What 2 data management policies does the data classification feature allow customers to classify in salesforce?
Choose 2 answers:
Answer: C,D
Explanation:
The data classification feature allows customers to classify their data in Salesforce based on two policies:
Data sensitivity level: This policy defines how sensitive the data is and what level of protection it requires. For example, high sensitivity data may require encryption or masking.
Compliance categorization policy: This policy defines how the data is regulated by various laws and standards. For example, GDPR or PCI DSS.
NEW QUESTION # 61
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