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Universal Containers (UC) has adopted Salesforce as its primary sales automated tool. UC has 100,00 customers with a growth rate of 10% a year, UC uses an on-premise web-based billing and invoice system that generates over 1 million invoices a year supporting a monthly billing cycle.
The UC sales team needs to be able to pull a customer record and view their account status, Invoice history, and opportunities without navigating outside of Salesforce.
What should a data architect use to provide the sales team with the required functionality?
To provide the sales team with the required functionality, a data architect should use a mashup page that will present the billing system records within Salesforce. A mashup page is a web page that combines data from multiple sources into a single integrated view. A mashup page can be created using Visualforce or Lightning Web Components, and can use Salesforce Connect or custom integrations to access external data from the on-premise web-based billing and invoice system. This will allow the sales team to pull a customer record and view their account status, invoice history, and opportunities without navigating outside of Salesforce. Option A is incorrect because creating a custom object and migrating the last 12 months of invoice data into Salesforce so it can be displayed on the account layout will consume a lot of storage space and may not reflect the latest data from the billing system. Option B is incorrect because writing an Apex callout and populating a related list to display on the account record will require additional development effort and may not be scalable or performant for large volumes of data. Option D is incorrect because creating a visual force tab with the billing system encapsulated within an iframe will not allow the sales team to view the billing system records within the customer record, but rather in a separate tab.
A large Automobile company has implemented SF for its Sales Associates. Leads flow from its website to SF using a batch integration in SF. The Batch job connects the leads to Accounts in SF. Customer visiting their retail stores are also created in SF as Accounts.
The company has noticed a large number of duplicate accounts in SF. On analysis, it was found that certain customers could interact with its website and also visit the store. The Sales associates use Global Search to search for customers in Salesforce before they create the customers.
Which scalable option should a data Architect choose to implement to avoid duplicates?
The data architect should choose to implement duplicate rules in SF (Salesforce) to validate duplicates during the account creation process. Duplicate rules are a feature in Salesforce that allow users to define criteria and actions for detecting and preventing duplicate records. By creating duplicate rules for accounts, the data architect can ensure that any leads from the website or customers from the retail stores that match existing accounts in Salesforce are flagged or blocked before they are created as new accounts. This will help avoid duplicate accounts in Salesforce and maintain data quality. Option B is incorrect because implementing a MDM (Master Data Management) solution to validate the customer information before creating accounts in SF will require additional infrastructure cost and maintenance effort. Option C is incorrect because building custom search based on fields on accounts which can be matched with customer when they visit the store will require additional development effort and may not be accurate or user-friendly. Option D is incorrect because customizing account creation process to search if customer exists before creating an account will require additional configuration effort and may not be consistent or scalable.
Northern Trail Outfitters (NTO) wants to start a loyalty program to reward repeat customers. The program will track every item a customer has bought and grants them points for discounts. The following conditions will exist upon implementation:
Data will be used to drive marketing and product development initiatives.
NTO estimates that the program will generate 100 million rows of date monthly.
NTO will use Salesforce's Einstein Analytics and Discovery to leverage their data and make business and marketing decisions.
What should the Data Architect do to store, collect, and use the reward program data?
Northern Trail Outfitters has these simple requirements for a data export process:
File format should be in CSV.
Process should be scheduled and run once per week.
The expert should be configurable through the Salesforce UI.
Which tool should a data architect leverage to accomplish these requirements?
The correct answer is B, data export wizard. The data export wizard is a tool that allows you to export your data in CSV format, schedule the export process to run once per week, and configure the export settings through the Salesforce UI. The data export wizard can handle up to 51 million records per export. The bulk API, third-party ETL tools, and data loader are also tools that can export data, but they are not as simple or user-friendly as the data export wizard.
UC has millions of case records with case history and SLA dat
a. UC's compliance team would like historical cases to be accessible for 10 years for Audit purpose.
What solution should a data architect recommend?
