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| Section | Objectives |
|---|---|
| Topic 1: Data Architecture and Design | - Handling large data volume and scalability considerations - Conceptual and logical data modeling - Data modeling best practices in Salesforce |
| Topic 2: Salesforce Data Model and Platform Capabilities | - Reporting and analytics considerations - Relationships and schema design - Standard and custom objects |
| Topic 3: Data Integration | - ETL vs ELT strategies - API-based integration approaches - Integration patterns in Salesforce |
| Topic 4: Data Migration | - Data cleansing and transformation - Data migration strategies and planning |
| Topic 5: Data Management | - Data governance principles - Master data management (MDM) concepts - Data quality management |
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NEW QUESTION # 146
Northern Trail Outfitter has implemented Salesforce for its associates nationwide, Senior management is concerned that the executive dashboard is not reliable for their real-time decision- making. On analysis, the team the following issues with data entered in Salesforce.
- Information in certain records is incomplete.
- Incorrect entry in certain fields causes records to be excluded in
report fitters.
- Duplicate entries cause incorrect counts.
Which three steps should a data architect recommend to address the issues?
Answer: B,C,E
Explanation:
According to the Salesforce documentation, data quality is the measure of how well the data in Salesforce meets the expectations and requirements of the users and stakeholders. Data quality can be affected by various factors, such as data entry errors, data duplication, data inconsistency, data incompleteness, data timeliness, etc. To address the issues with data quality that affect the reliability of executive dashboards, a data architect should recommend:
Building a sales data warehouse with purpose-built data marts for dashboards and senior management reporting (option B). This means creating a separate database or system that stores and organizes sales data from Salesforce and other sources for analytical purposes. A data warehouse can provide a single source of truth for sales data and enable faster and more accurate reporting and analysis. A data mart is a subset of a data warehouse that focuses on a specific subject or business area, such as sales performance, customer segmentation, product profitability, etc. A data mart can provide tailored and relevant data for different users or groups based on their needs and interests.
Exploring third-party data providers to enrich and augment information entered in Salesforce (option C). This means using external services or tools that can validate, correct, update, and enhance the data that is entered or imported into Salesforce. This can help improve data quality and accuracy, and reduce data duplication and incompleteness.
Leveraging Salesforce features, such as validation rules, to avoid incomplete and incorrect records (option D). This means using features that allow defining rules and criteria to validate the data that is entered or updated by the users or integrations. This can help prevent invalid or incorrect data from being saved, and trigger actions or alerts to correct or improve the data.
NEW QUESTION # 147
Universal Containers has more than 10 million records in the Order_c object. The query has timed out when running a bulk query. What should be considered to resolve query timeout?
Answer: C
Explanation:
PK Chunking can resolve query timeout when running a bulk query on an object with more than
10 million records. PK Chunking is a feature of the Bulk API that splits a query into multiple batches based on the record IDs (primary keys) of the queried object. This can improve the query performance and avoid timeouts by reducing the number of records processed in each batch.
NEW QUESTION # 148
Universal Containers (UC) is implementing a formal, cross -business -unit data governance program As part of the program, UC will implement a team to make decisions on enterprise -wide data governance. Which two roles are appropriate as members of this team? Choose 2 answer
Answer: C,D
Explanation:
Analytics/BI Owners and Data Domain Stewards are appropriate roles as members of a team that makes decisions on enterprise-wide data governance. Analytics/BI Owners are responsible for defining the business requirements and metrics for data analysis and reporting, and Data Domain Stewards are responsible for defining and enforcing the data quality standards and rules for specific data domains. Salesforce Administrators and Operational Data Users are not suitable roles for this team, as they are more focused on the operational aspects of data management, such as configuration, maintenance, and usage.
NEW QUESTION # 149
Universal Containers has a large volume of Contact data going into Salesforce.com. There are
100,000 existing contact records. 200,000 new contacts will be loaded. The Contact object has an external ID field that is unique and must be populated for all existing records. What should the architect recommend to reduce data load processing time?
Answer: A
Explanation:
Loading new records via the Insert operation and existing records via the Update operation will allow using the external ID field as a unique identifier and avoid any duplication or overwriting of records. This is faster and safer than deleting all existing records or using the Upsert operation, which might cause conflicts or errors .
NEW QUESTION # 150
Universal Containers (UC) has several custom Visualforce applications have been developed in which users are able to edit Opportunity records. UC struggles with data completeness on their Opportunity records and has decided to make certain fields required that have not been in the past. The newly required fields are dependent on the Stage of the Opportunity, such that certain fields are only required once an Opportunity advances to later stages. There are two fields. What is the simplest approach to handle this new requirement?
Answer: D
Explanation:
Using a validation rule for each field that takes the Stage into consideration is the simplest approach to handle this new requirement. A validation rule can enforce the field requirements based on the logic and criteria that you define, and display an error message when users try to save a record that does not meet the requirements. Updating the Opportunity page layout to mark these fields as required will not work because page layouts do not support conditional field requirements. Updating these Opportunity field definitions in Setup to be required will not work because it will apply to all stages and records. Writing an Apex trigger that checks each field when records are saved is not the simplest approach because it requires coding and testing
NEW QUESTION # 151
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