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| Section | Weight | Objectives |
|---|---|---|
| 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 - Handling locks and parallelism during migration - API-based integration (REST, SOAP, Bulk API) - Real-time vs batch integration patterns |
| Data Modeling | 25% | - Large Data Volumes (LDV) design considerations - Big Objects and external objects - Normalization and denormalization strategies - Indexing strategies - Skinny tables for performance optimization |
| Data Architecture | 20% | - Archiving and data lifecycle management - Governor limits and bulk processing - Architecture patterns and design principles - Performance tuning and optimization |
| Data Governance | 20% | - Data retention and archiving policies - Data quality standards and metrics - Data stewardship roles and responsibilities - Compliance and regulatory considerations |
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NEW QUESTION # 21
North Trail Outfitters (NTO) operates a majority of its business from a central Salesforce org, NTO also owns several secondary orgs that the service, finance, and marketing teams work out of, At the moment, there is no integration between central and secondary orgs, leading to data-visibility issues.
Moving forward, NTO has identified that a hub-and-spoke model is the proper architect to manage its data, where the central org is the hub and the secondary orgs are the spokes.
Which tool should a data architect use to orchestrate data between the hub org and spoke orgs?
Answer: B
Explanation:
According to the Salesforce documentation, a hub-and-spoke model is an integration architecture pattern that allows connecting multiple Salesforce orgs using a central org (hub) and one or more secondary orgs (spokes).
The hub org acts as the master data source and orchestrates the data flow between the spoke orgs. The spoke orgs act as the consumers or producers of the data and communicate with the hub org.
To orchestrate data between the hub org and spoke orgs, a data architect should use:
A middleware solution that extracts and distributes data across both the hub and spokes (option A). This means using an external service or tool that can connect to multiple Salesforce orgs using APIs or connectors, and perform data extraction, transformation, and distribution operations between the hub and spoke orgs. This can provide a scalable, flexible, and reliable way to orchestrate data across multiple orgs.
Developing custom APIs to poll the hub org for change data and push into the spoke orgs (option B) is not a good solution, as it can be complex, costly, and difficult to maintain. It may also not be able to handle large volumes of data or complex transformations efficiently. Developing custom APIs to poll the spoke orgs for change data and push into the hub org (option C) is also not a good solution, as it can have the same drawbacks as option B. It may also not be able to handle conflicts or errors effectively. Using a backup and archive solution that extracts and restores data across orgs (option D) is also not a good solution, as it can incur additional costs and dependencies. It may also not be able to handle real-time or near-real-time data orchestration requirements.
NEW QUESTION # 22
Universal Containers wants to implement a data -quality process to monitor the data that users are manually entering into the system through the Salesforce UI. Which approach should the architect recommend?
Answer: B
Explanation:
Utilizing an app from the AppExchange to create data-quality dashboards is the approach that the architect should recommend for UC to implement a data-quality process to monitor the data that users are manually entering into the system through the Salesforce UI. An app from the AppExchange can provide ready-made or customizable dashboards that can display various metrics and indicators of data quality, such as completeness, accuracy, consistency, timeliness, etc. These dashboards can help UC to measure and evaluate their data quality performance and identify any areas that need improvement or attention. The other options are not relevant or effective for implementing a data-quality process, as they would either not address the issue of manual data entry, not provide data-quality monitoring, or not leverage the benefits of Salesforce.
NEW QUESTION # 23
Get Cloudy Consulting needs to evaluate the completeness and consistency of contact information in Salesforce. Their sales reps often have incomplete information about their accounts and contacts.
Additionally, they are not able to interpret the information in a consistent manner. Get Cloudy Consulting has identified certain " " key " " fields which are important to their sales reps.
What are two actions Get Cloudy Consulting can take to review their data for completeness and consistency?
(Choose two.)
Answer: B,D
Explanation:
Running a report that shows the last time the key fields were updated can help Get Cloudy Consulting identify stale or outdated data and prioritize data cleansing activities. Running a report that shows the percentage of blanks for the important fields can help Get Cloudy Consulting measure the completeness of their data and identify gaps or missing value
NEW QUESTION # 24
Universal Containers has a large number of Opportunity fields (100) that they want to track field history on.
Which two actions should an architect perform in order to meet this requirement? Choose 2 answers
Answer: A,D
Explanation:
Creating a custom object to store a copy of the record when changed and creating a custom object to store the previous and new field values are two possible actions that an architect can perform to meet the requirement of tracking field history on 100 Opportunity fields. A custom object can store more fields and records than the standard field history tracking feature, which has a limit of 20 fields per object and 18 or 24 months of data retention. A custom object can also be used for reporting and analysis of field history data. The other options are not feasible or effective for meeting the requirement
NEW QUESTION # 25
UC has one SF org (Org A) and recently acquired a secondary company with its own Salesforce org (Org B).
UC has decided to keep the orgs running separately but would like to bidirectionally share opportunities between the orgs in near-real time.
Which 3 options should a data architect recommend to share data between Org A and Org B?
Choose 3 answers.
Answer: A,C,E
Explanation:
Leveraging Heroku Connect and Heroku Postgres, middleware tools, or Salesforce Connect and the cross-org adapter are all viable options to share data between Org A and Org B in near-real time3. Installing a 3rd party AppExchange tool may not provide bidirectional sync or may have additional costs. Developing an Apex class that pushes opportunity data between orgs daily via the Apex schedule may not meet the near-real time requirement.
NEW QUESTION # 26
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