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Salesforce Certified Data Architect Exam
- Topic 1: 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 2: Master Data Management: This topic covers the various techniques, approaches, and considerations to implement Master Data Management Solutions, and techniques for establishing a "golden record" or "system of truth" for the customer domain. It also discusses approaches and techniques for consolidating data attributes and maintaining customer reference and metadata.
- Topic 3: 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 4: 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 as well different approaches and considerations to design and implement an enterprise data governance program.
- Topic 5: Large Data Volume considerations: It 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 virtualised data options.
- Topic 6: Data Migration: This topic covers suitable techniques and methods to make sure high data quality at load time, different strategies to improve performance when migrating large data volumes into Salesforce, and various techniques and considerations to export data from Salesforce.
Free Salesforce Salesforce Certified Data Architect Exam Actual Questions
The questions for Salesforce Certified Data Architect were last updated On Apr. 06, 2024
Northern Trail Outfitters needs to implement an archive solution for Salesforce dat
a. This archive solution needs to help NTO do the following:
1. Remove outdated Information not required on a day-to-day basis.
2. Improve Salesforce performance.
Which solution should be used to meet these requirements?
Identifying a location to store archived data and using scheduled batch jobs to migrate and purge the aged data on a nightly basis can be a way to meet the requirements for an archive solution. The article provides a use case of how to use Heroku Connect, Postgres, and Salesforce Connect to archive old data, free up space in the org, and still retain the option to unarchive the data if needed. The article also explains how this solution can improve Salesforce performance and meet data retention policies.
Northern Trail Outfitters (NTO) has multiple Salesforce orgs based on regions. Users need read-only access to customers across all Salesforce orgs.
Which feature in Salesforce can be used to provide access to customer records across all NTO orgs?
Salesforce Connect is a feature that allows users to access data from external sources and multiple Salesforce orgs, using either clicks or code. Salesforce Connect can provide read-only access to customer records across all NTO orgs, without replicating or storing the data in Salesforce.
Which API should a data architect use if exporting 1million records from Salesforce?
Using Bulk API to export 1 million records from Salesforce is the best option. Bulk API is a RESTful API that allows you to perform asynchronous operations on large sets of data. You can use Bulk API to create, update, delete, or query millions of records in batches. Bulk API is optimized for performance and scalability, and it can handle complex data loading scenarios.
Universal Containers (UC) has 50 million customers and stores customer order history on an ERP system. UC also uses Salesforce to manage opportunities and customer support.
In order to provide seamless customer support, UC would like to see the customer's order history when viewing the customer record during a sales or support call.
What should a data architect do in order to provide this functionality, while preserving the user experience?
Universal Containers has implemented Salesforce for its operations. In order for customers to be created in their MDM solution, the customer record needs to have the following attributes:
1. First Name
2. Last Name
3. Email
Which option should the data architect recommend to mandate this when customers are created in Salesforce?
Creating validation rules to check if the required attributes are entered is the best option to mandate this when customers are created in Salesforce. Validation rules allow you to specify criteria that must be met before a record can be saved. You can use validation rules to ensure that customers have a first name, last name, and email when they are created in Salesforce. This way, you can prevent incomplete or invalid data from being sent to your MDM solution.
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adam zampa
24 days ago