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Universal Containers (UC) owns several Salesforce orgs across a variety of business units. UC management has declared that it needs the ability to report on Accounts and Opportunities from each org in one place. Once the data is brought together into a global view, management would like to use advanced Al-driven analytics on the dataset.
Which tool should a data architect recommend to accomplish this reporting requirement?
According to this article, Einstein Analytics for multi-org can help UC to report on accounts and opportunities from each org in one place. It can also provide advanced AI-driven analytics on the dataset using Einstein Discovery.
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.)
Running a report that shows the last time the key fields were updated can help Get Cloudy Consulting identify stale or outdated data and prioritize data cleansing activities.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
US has released a new disaster recovery (DR)policy that states that cloud solutions need a business continuity plan in place separate from the cloud providers built in data recovery solution.
Which solution should a data architect use to comply with the DR policy?
The best solution to comply with the DR policy is to leverage a 3rd party tool that extract Salesforce data/metadata and stores the information in an external protected system. This solution can help create a backup of Salesforce data and metadata in case of a disaster or data loss event. It can also help restore data from the backup system to Salesforce if needed. There are various 3rd party tools available in the AppExchange or online that offer data backup and recovery services for Salesforce67. Leverage Salesforce weekly exports and store data in flat files on a protected system is not a good solution because it does not include metadata backup and it does not allow granular or automated data recovery. Utilize an ETL tool to migrate data to an on-premise archive solution is not a good solution because it does not include metadata backup and it may require complex data transformations and synchronizations. Write a custom batch job to extract data changes nightly and store in an external protected system is not a good solution because it does not include metadata backup and it may have performance or reliability issues.
Universal Containers (CU) is in the process of implementing an enterprise data warehouse (EDW). UC needs to extract 100 million records from Salesforce for migration to the EDW.
What data extraction strategy should a data architect use for maximum performance?
According to the Salesforce documentation2, extracting large amounts of data from Salesforce can be challenging and time-consuming, as it can encounter performance issues, API limits, timeouts, etc. To extract 100 million records from Salesforce for migration to an enterprise data warehouse (EDW), a data extraction strategy that can provide maximum performance is:
Utilize PK Chunking with the Bulk API (option C). This means using a feature that allows splitting a large query into smaller batches based on the record IDs (primary keys) of the queried object. This can improve performance and avoid timeouts by processing each batch asynchronously and in parallel using the Bulk API3.
Installing a third-party AppExchange tool (option A) is not a good solution, as it can incur additional costs and dependencies. It may also not be able to handle such a large volume of data efficiently. Calling the REST API in successive queries (option B) is also not a good solution, as it can encounter API limits and performance issues when querying such a large volume of data. Using the Bulk API in parallel mode (option D) is also not a good solution, as it can still cause timeouts and errors when querying such a large volume of data without chunking.
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.
