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| Section | Weight | Objectives |
|---|---|---|
| Data Architecture | 20% | - Archiving and data lifecycle management - Performance tuning and optimization - Architecture patterns and design principles - Governor limits and bulk processing |
| Data Modeling | 25% | - Big Objects and external objects - Skinny tables for performance optimization - Large Data Volumes (LDV) design considerations - Normalization and denormalization strategies - Indexing strategies |
| Data Governance | 20% | - Compliance and regulatory considerations - Data retention and archiving policies - Data quality standards and metrics - Data stewardship roles and responsibilities |
| Master Data Management | 20% | - Identity resolution - Data cleansing techniques - Data duplication and matching rules |
| Data Integration | 15% | - ETL tools and data migration strategies - Sharing rules impact on data integration - Real-time vs batch integration patterns - API-based integration (REST, SOAP, Bulk API) - Handling locks and parallelism during migration |
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NEW QUESTION # 244
UC is preparing to implement sales cloud and would like to its users to have read only access to an account record if they have access to its child opportunity record. How would a data architect implement this sharing requirement between objects?
Answer: C
Explanation:
Implicit sharing will automatically handle this sharing requirement with standard functionality, as it grants read-only access to parent accounts when users have access to child opportunities. This is also known as account-opportunity sharing3. Creating a criteria-based sharing rule (option A) or an owner-based sharing rule (option D) is not necessary, as they are used to grant additional access based on record criteria or ownership. Adding appropriate users to the account team (option C) is also not required, as it is used to grant access to specific users or groups for individual accounts.
NEW QUESTION # 245
Northern Trail Outfitters (NTO) wants to capture a list of customers that have bought a particular product. The solution architect has recommended to create a custom object for product, and to create a lookup relationship between its customers and its products.
Products will be modeled as a custom object (NTO_ Product__ c) and customers are modeled as person accounts. Every NTO product may have millions of customers looking up a single product, resulting in a lookup skew.
What should a data architect suggest to mitigate Issues related to lookup skew?
Answer: C
Explanation:
creating multiple similar products and distributing the skew across those products can be a way to mitigate issues related to lookup skew. The article explains that lookup skew happens when a very large number of records are associated with a single record in the lookup object, and this can cause record locking and performance issues. The article suggests creating multiple copies of the same product record and assigning different child records to each copy, so that the number of child records per parent record is reduced.
NEW QUESTION # 246
Northern Trail Outfitters (NTO) has the following systems:
Customer master-source of truth for customer information
Service cloud-customer support
Marketing cloud-marketing support
Enterprise data warehouse-business reporting
The customer data is duplicated across all these systems and are not kept in sync. Customers are also complaining that they get repeated marketing emails and have to call into update their information.
NTO is planning to implement master data management (MDM) solution across the enterprise.
Which three data will an MDM tool solve?
Choose 3 answers
Answer: A,C,D
Explanation:
According to the What is Master Data Management (MDM)? article, some of the data challenges that an MDM tool can solve are data duplication, data accuracy and quality, and data standardization. The article states that "MDM solutions comprise a broad range of data cleansing, transformation, and integration practices. As data sources are added to the system, MDM initiates processes to identify, collect, transform, and repair data. Once the data meets the quality thresholds, schemas and taxonomies are created to help maintain a high-quality master reference." Therefore, an MDM tool can help NTO eliminate data duplication across different systems, improve data accuracy and quality by removing errors and inconsistencies, and standardize data formats and definitions for better integration and analysis.
NEW QUESTION # 247
Universal Container is using Salesforce for Opportunity management and enterprise resource planning (ERP) for order management. Sales reps do not have access to the ERP and have no visibility into order status.
What solution a data architect recommends to give the sales team visibility into order status?
Answer: C
NEW QUESTION # 248
Cloud Kicks needs to purge detailed transactional records from Salesforce. The data should be aggregated at a summary level and available in Salesforce.
What are two automated approaches to fulfill this goal? (Choose two.)
Answer: C,D
NEW QUESTION # 249
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