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| Section | Objectives |
|---|---|
| Topic 1: Data Integration | - Integration patterns in Salesforce - ETL vs ELT strategies - API-based integration approaches |
| Topic 2: Data Management | - Data quality management - Data governance principles - Master data management (MDM) concepts |
| Topic 3: Data Migration | - Data migration strategies and planning - Data cleansing and transformation |
| Topic 4: Salesforce Data Model and Platform Capabilities | - Standard and custom objects - Reporting and analytics considerations - Relationships and schema design |
| Topic 5: Data Architecture and Design | - Handling large data volume and scalability considerations - Data modeling best practices in Salesforce - Conceptual and logical data modeling |
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NEW QUESTION # 114
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: B
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. 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.
Asking SF support to increase the query timeout value is not feasible because query timeout values are not configurable
NEW QUESTION # 115
Universal Containers is exporting 40 million Account records from Salesforce using Informatica Cloud. The ETL tool fails and the query log indicates a full table scan time-out failure. What is the recommended solution?
Answer: C
Explanation:
The Sforce-Enable-PKChunking header enables you to extract large data sets from Salesforce by using a technique called primary key (PK) chunking. PK chunking splits your query into multiple queries based on the record IDs of the queried object. This reduces the query time and avoids the query timeout issues that can occur with large data volumes
NEW QUESTION # 116
Universal Containers is establishing a call center that will use Salesforce. UC receives 10 million calls and creates 100 million cases every month. Cases are linked to a custom call object using lookup relationship. UC would like to run reports and dashboard to better understand different case types being created on calls to better serve customers. What solution should a data architect recommend to meet the business requirement?
Answer: A
Explanation:
According to this article, big objects can store and manage massive amounts of data on the Salesforce platform. This can help UC to archive records from other objects or bring massive datasets from outside systems into a big object. According to this article, Einstein Analytics can be used to create dashboards and lenses to analyze big object data and get insights from advanced AI-driven analytics.
NEW QUESTION # 117
Universal Container (UC) has accumulated data over years and has never deleted data from its Salesforce org. UC is now exceeding the storage allocations in the org. UC is now looking for option to delete unused from the org. Which three recommendations should a data architect make is order to reduce the number of records from the org? Choose 3 answer
Answer: A,C,E
Explanation:
Using hard delete in Bulk API, identifying records that have not been modified or used in last 3 years, and archiving the records in EDW before deleting from Salesforce are all good recommendations to reduce the number of records from the org. Using hard delete in batch Apex or Rest API may not be as efficient or scalable as Bulk API
NEW QUESTION # 118
NTO has multiple systems across its enterprise landscape including salesforce, with disparate version the customer records.
In salesforce, the customer is represented by the contact object.
NTO utilizes an MDM solution with these attributes:
1. The MDM solution keeps track of customer master with a master key.
2. The master key is a map to the record ID's from each external system that customer data is stored within.
3. The MDM solution provides de-duplication features, so it acts as the single source of truth.
How should a data architect implement the storage of master key within salesforce?
Answer: D
Explanation:
The best way to implement the storage of master key within Salesforce is to store it on the contact object as an external ID field for referential imports. This way, the data architect can use the master key as a unique identifier to match records from different systems and avoid duplicates. The other options are not feasible because they either require additional storage or do not support referential imports.
NEW QUESTION # 119
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