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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Modeling | 25% | - Normalization and denormalization strategies - Big Objects and external objects - Large Data Volumes (LDV) design considerations - Indexing strategies - Skinny tables for performance optimization |
| Topic 2: Data Integration | 15% | - ETL tools and data migration strategies - API-based integration (REST, SOAP, Bulk API) - Handling locks and parallelism during migration - Sharing rules impact on data integration - Real-time vs batch integration patterns |
| Topic 3: Master Data Management | 20% | - Identity resolution - Data cleansing techniques - Data duplication and matching rules |
| Topic 4: Data Governance | 20% | - Data retention and archiving policies - Compliance and regulatory considerations - Data stewardship roles and responsibilities - Data quality standards and metrics |
| Topic 5: Data Architecture | 20% | - Performance tuning and optimization - Architecture patterns and design principles - Governor limits and bulk processing - Archiving and data lifecycle management |
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NEW QUESTION # 195
A manager at Cloud Kicks is importing Leads into Salesforce and needs to avoid creating duplicate records.
Which two approaches should the manager take to achieve this goal? (Choose two.)
Answer: A,D
NEW QUESTION # 196
UC is rolling out Sales App globally to bring sales teams together on one platform. UC expects millions of opportunities and accounts to be creates and is concerned about the performance of the application.
Which 3 recommendations should the data architect make to avoid the data skew? Choose 3 answers.
Answer: B,C,E
Explanation:
Data skew occurs when a large number of child records are associated with a single parent record, or when a single user owns a large number of records. This can cause performance issues and lock contention. To avoid data skew, the data architect should limit assigning one user 10,000 records ownership, limit associating 10,000 opportunities to one account, and limit associating 10,000 records looking up to the same record
NEW QUESTION # 197
Universal Containers (UC) is expecting to have nearly 5 million shipments records in its Salesforce org. Each shipment record has up to 10 child shipment item records. The Shipment custom object has an Organization-wide Default (OWD) sharing model set to Private and the Shipment Item custom object has a Master-Detail relationship to Shipment. There are 25 sharing rules set on the Shipment custom object, which allow shipment records to be shared to each of UC's 25 business areas around the globe. These sharing rules use public groups, one for each business area plus a number of groups for management and support roles. UC has a high turnover of Sales Reps and often needs to move Sales Reps between business areas in order to meet local demand. What feature would ensure that performance, when moving Sales Reps between regions, remains adequate while meeting existing requirements?
Answer: D
Explanation:
Contacting Salesforce to enable Defer Sharing Rules is the feature that would ensure that performance, when moving Sales Reps between regions, remains adequate while meeting existing requirements. Defer Sharing Rules allows you to defer sharing rule recalculation when you make changes to public groups or roles that are used in sharing rules. This can improve performance and avoid locking issues when you move users between groups or roles2. Implementing data archiving for old Shipment records will not help with the performance issue related to sharing rules. Contacting Salesforce to create Skinny tables on Shipment will not help with the performance issue related to sharing rules. Configuring shipment OWD to Public Read/Write will not meet the existing requirements of having a Private sharing model.
NEW QUESTION # 198
Universal Containers has multiple systems all containing and maintaining customer dat a. Although point-to-point integrations are in place, customers are complaining about consistency in the data.
What solution should the data architect recommend?
Answer: A
Explanation:
Master data management (MDM) is a solution that helps organizations manage their master data across multiple systems and ensure consistency and quality. An MDM solution can act as the customer master, with centralized integrations to other systems, to avoid data duplication and inconsistency.
NEW QUESTION # 199
What makes Skinny tables fast? Choose three answers.
Answer: A,D,E
Explanation:
Skinny tables are custom tables that contain frequently used fields from a standard or custom object. They are used to improve performance by reducing the number of database joins required for queries. Skinny tables have the following characteristics1:
They do not include soft-deleted records, which means they only contain active records and save space.
They avoid resource intensive joins by storing data from multiple objects in one table, which reduces the query time and complexity.
Their tables are kept in sync with their source tables when the source tables are modified, which ensures data consistency and accuracy.
NEW QUESTION # 200
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