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| Section | Weight | Objectives |
|---|---|---|
| Data Integration | 20% | - Data synchronization and consistency
|
| Master Data Management | 5% | - MDM implementation approaches
|
| Data Governance, Quality and Security | 15% | - Data security and compliance
|
| Large Data Volumes and Performance | 20% | - Storage and scalability planning
|
| Data Modeling and Database Design | 25% | - Data model design for Customer 360
|
| Data Migration | 15% | - Data quality and validation
|
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NEW QUESTION # 108
In their legacy system. Universal Containers has a monthly accounts receivable report that compiles data from Accounts, Contacts, Opportunities, Orders. and Order Line Items. What difficulty will an architect run into when implementing this in Salesforce?
Answer: D
Explanation:
Salesforce allows up to four objects in a single report type. This means that if an architect wants to create a report that compiles data from Accounts, Contacts, Opportunities, Orders, and Order Line Items, they will run into a difficulty because that would require five objects in a single report type. To overcome this limitation, the architect can either create two separate report types and join them in a joined report, or use an external reporting tool that can access data from multiple objects.
NEW QUESTION # 109
UC has a variety of systems across its technology landscape, including SF, legacy enterprise resource planning (ERP) applications and homegrown CRM tools. UC has decided that they would like to consolidate all customer, opportunity and order data into Salesforce as part of its master data management (MDM) strategy. What are the 3 key steps that a data architect should take when merging data from multiple systems into Salesforce? Choose 3 answer
Answer: A,B,D
Explanation:
The three key steps that a data architect should take when merging data from multiple systems into Salesforce are:
Analyze each system's data model and perform gap analysis. This step involves understanding the structure and meaning of the data in each system, identifying the common and unique data elements, and mapping the data fields between the systems. This step also involves assessing the quality and consistency of the data, and identifying any data cleansing or transformation needs.
Utilize an ETL tool to merge, transform, and de-duplicate data. This step involves using an ETL tool to connect to the source systems, extract the data, apply any data transformations or validations, and load the data into Salesforce. This step also involves applying de-duplication rules or algorithms to avoid creating duplicate records in Salesforce.
Work with stakeholders to define record and field survivorship rules. This step involves collaborating with the business users and owners of the data to determine which records and fields should be retained or overwritten in case of conflicts or discrepancies. This step also involves defining the criteria and logic for record and field survivorship, and implementing them in the ETL tool or in Salesforce.
Creating new fields to store additional values from all the systems is not a key step, but rather a possible outcome of the gap analysis. It may not be necessary or desirable to create new fields for every value from every system, as it may result in redundant or irrelevant data. Installing a 3rd party AppExchange tool to handle the merger is not a key step, but rather a possible option for choosing an ETL tool. It may not be the best option depending on the requirements, budget, and preferences of the organization.
NEW QUESTION # 110
What 2 data management policies does the data classification feature allow customers to classify in salesforce? Choose 2 answer
Answer: A,B
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 # 111
Universal Containers has two systems. Salesforce and an on-premise ERP system. An architect has been tasked with copying Opportunity records to the ERP once they reach a Closed/Won Stage. The Opportunity record in the ERP system will be read-only for all fields copied in from Salesforce. What is the optimal real-time approach that achieves this solution?
Answer: A
Explanation:
Implementing a workflow rule that sends Opportunity data through Outbound Messaging is the optimal real-time approach that achieves the solution of copying Opportunity records to the ERP once they reach a Closed/Won Stage. A workflow rule can trigger an Outbound Message when an Opportunity record meets certain criteria, such as having a Closed/Won Stage. An Outbound Message can send data from Salesforce to an external system via SOAP API, without requiring any code. The external system can then process the data and create a read-only record in the ERP system. The other options are not optimal or real-time, as they would either require additional systems or tools, not provide real-time data synchronization, or not meet the frequency requirement
NEW QUESTION # 112
An architect has been asked by a client to develop a solution that will integrate data and resolve duplicates and discrepancies between Salesforce and one or more external systems. What two factors should the architect take into consideration when deciding whether or not to use a Master Data Management system to achieve this solution? Choose 2 answer
Answer: A,D
Explanation:
Whether the system of record changes for different tables and the number of systems that are integrating with each other are two factors that the architect should take into consideration when deciding whether or not to use a Master Data Management system to achieve the solution of integrating data and resolving duplicates and discrepancies between Salesforce and one or more external systems. The system of record is the authoritative source of truth for a given entity or field in a given context. If different systems have different systems of record for different tables, then a Master Data Management system can help to manage and synchronize the data across systems and ensure data quality and consistency. The number of systems that are integrating with each other is another factor that affects the complexity and scalability of the integration solution. If there are many systems that need to integrate with each other, then a Master Data Management system can provide a centralized and standardized way of integrating data and resolving duplicates and discrepancies across systems. The other factors are not relevant or important for deciding whether or not to use a Master Data Management system, as they do not affect the data quality or integration challenges that a Master Data Management system can address.
NEW QUESTION # 113
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