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Salesforce Data-Architect Certification will help you achieve a better understanding of the Salesforce platform and become a master of data architecture. Salesforce Certified Data Architect certification requires you to have an in-depth knowledge of Salesforce data architecture concepts, best practices, and implementation. You'll learn how to create a scalable, performant, and maintainable data architecture for your organization's goals.

Salesforce Data-Architect Exam Syllabus Topics:

TopicDetails
Topic 1
  • Salesforce Data Management: This topic covers the appropriate combination of Salesforce license types, techniques to ensure data is persisted in a consistent manner, and approaches to represent a single view of the customer on the Salesforce platform. It also covers techniques to effectively consolidate and leverage data from multiple Salesforce instances.
Topic 2
  • Data modeling
  • Database Design: This topic covers various techniques and considerations for designing a data model for the Customer 360 platform. It also focuses on approaches to designing a scalable data model that obeys the current security and sharing model. The topic also compares and contrasts techniques for capturing and managing business and technical metadata, as well as the reasons for implementing Big Objects vs Standard
  • Custom objects and approaches to avoid data skew.
Topic 3
  • Data Governance: This topic covers the approach for designing a GDPR-compliant data model, including identifying, classifying, and protecting personal and sensitive information. It also delves into different approaches and considerations for designing and implementing an enterprise data governance program.
Topic 4
  • Large Data Volume Considerations: This covers the design of a data model that scales considering large data volume and solution performance, a data archiving and purging plan, and the use of virtualized data options.

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Salesforce Certified Data Architect Sample Questions (Q188-Q193):

NEW QUESTION # 188
Universal Containers has millions of rows of data in Salesforce that are being used in reports to evaluate historical trends. Performance has become an issue, as well as data storage limits. Which two strategies should be recommended when talking with stakeholders?

Answer: B,D

Explanation:
Using scheduled batch Apex to copy aggregate information into a custom object and delete the original records can improve the performance and reduce the data storage limits by removing unnecessary data and keeping only the summary data that is needed for reporting. Configuring the Salesforce Archiving feature to archive older records and remove them from the data storage limits can also help with performance and storage issues by moving historical data to a separate system that is still accessible but does not affect the operational data


NEW QUESTION # 189
Universal Containers (UC) has implemented Sales Cloud and it has been noticed that Sales reps are not entering enough data to run insightful reports and dashboards. UC executives would like to monitor and measure data quality metrics. What solution addresses this requirement?

Answer: A


NEW QUESTION # 190
NTO need to extract 50 million records from a custom object everyday from its Salesforce org. NTO is facing query timeout issues while extracting these records.
What should a data architect recommend in order to get around the time out issue?

Answer: D

Explanation:
The best solution to extract 50 million records from a custom object everyday from Salesforce org without facing query timeout issues is to use an ETL tool for extraction of records. ETL stands for extract, transform, and load, and it refers to a process of moving data from one system to another. An ETL tool is a software application that can connect to various data sources, perform data transformations, and load data into a target destination. ETL tools can handle large volumes of data efficiently and reliably, and they often provide features such as scheduling, monitoring, error handling, and logging 5 . Using a custom auto number and formula field and use that to chunk records while extracting data is a possible workaround, but it requires creating additional fields and writing complex queries. The REST API can extract data as it automatically chunks records by 200, but it has some limitations, such as a maximum of 50 million records per query job 6
. Asking SF support to increase the query timeout value is not feasible because query timeout values are not configurable


NEW QUESTION # 191
A company has 12 million records, and a nightly integration queries these records.
Which two areas should a Data Architect investigate during troubleshooting if queries are timing out?
(Choose two.)

Answer: B,C

Explanation:
Making sure the query does not contain NULL in any filter criteria can avoid full table scans and leverage indexes more efficiently. Queries with NULL filters are not selective and can cause performance issues.
Creating custom indexes on the fields used in the filter criteria can also enhance the query performance by reducing the number of records to scan.


NEW QUESTION # 192
UC has a legacy client server app that as a relational data base that needs to be migrated to salesforce.
What are the 3 key actions that should be done when data modeling in salesforce?
Choose 3 answers:

Answer: B,C,D


NEW QUESTION # 193
......

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