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| Section | Weight | Objectives |
|---|
| Data Integration | 20% | - Integration patterns and technologies
- 1. APIs, middleware and external systems integration
- 2. Synchronous vs asynchronous, batch vs real-time
- Data synchronization and consistency
- 1. Conflict resolution, data consistency and idempotency
- External data sources
- 1. External Objects, OData and virtual data access
|
| Master Data Management | 5% | - Golden record and system of truth
- 1. Establishing single source of truth in single org
- MDM implementation approaches
- 1. Canonical modeling and hierarchy management
- 2. Harmonization, consolidation, survivorship rules and thresholds
|
| Data Modeling and Database Design | 25% | - Object type selection
- 1. Standard/custom objects vs Big Objects: use cases, pros and cons
- Metadata management
- 1. Business dictionary, data lineage, taxonomy and classification
- Data model design for Customer 360
- 1. Objects, fields, relationships and object features
- 2. Scalable design aligned with security and sharing model
- Data skew prevention
- 1. Avoid record locking, sharing issues and excessive parent-child relationships
|
| Large Data Volumes and Performance | 20% | - Query and performance optimization
- 1. Indexing, selective queries and avoiding performance bottlenecks
- Storage and scalability planning
- 1. Data volume growth planning and storage limits
- LDV architecture design
- 1. Data distribution, archiving and partitioning strategies
|
| Data Governance, Quality and Security | 15% | - Data quality management
- 1. Profiling, monitoring, cleansing and enrichment
- Data security and compliance
- 1. Access control, encryption, compliance and audit
- Data governance framework
- 1. Policies, standards, ownership and stewardship
|
| Data Migration | 15% | - Migration strategy and planning
- 1. Assessment, mapping, validation and rollback planning
- Data quality and validation
- 1. Cleaning, deduplication and post-migration verification
- Migration execution and tools
- 1. Data loader, ETL tools and bulk API usage
|
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Salesforce Certified Platform Data Architect Sample Questions (Q255-Q260):
NEW QUESTION # 255
NTO processes orders from its website via an order management system (OMS). The OMS stores over 2 million historical records and is currently not integrated with SF. The Sales team at NTO using Sales cloud and would like visibility into related customer orders yet they do not want to persist millions of records directly in Salesforce. NTO has asked the data architect to evaluate SF connect and the concept of data verification. Which 3 considerations are needed prior to a SF Connect implementation? Choose 3 answer
- A. Configure a middleware tool to poll external table data
- B. Assess whether the external data source is reachable via an ODATA endpoint.
- C. Develop an object relationship strategy.
- D. Identify the external tables to sync into external objects
- E. Create a 2nd system Admin user for authentication to the external source.
Answer: B,C,D
Explanation:
The three considerations needed prior to a SF Connect implementation are to develop an object relationship strategy, identify the external tables to sync into external objects, and assess whether the external data source is reachable via an ODATA endpoint. SF Connect is a feature that allows integrating external data sources with Salesforce using external objects. External objects are similar to custom objects, but they store metadata only and not data. They enable on-demand access to external data via standard Salesforce APIs and user interfaces. To implement SF Connect, a data architect needs to consider how the external objects will relate to other objects in Salesforce, which external tables will be exposed as external objects, and whether the external data source supports ODATA protocol for data access.
NEW QUESTION # 256
Northern Trail Outfitters (NTO) has recently implemented Salesforce to track opportunities across all their regions. NTO sales teams across all regions have historically managed their sales process in Microsoft Excel. NTO sales teams are complaining that their data from the Excel files were not migrated as part of the implementation and NTO is now facing low Salesforce adoption.
What should a data architect recommend to increase Salesforce adoption?
- A. Use the Excel connector to Salesforce to sync data from individual Excel files.
- B. Define a standard mapping and train sales users to import opportunity data.
- C. Load data in external database and provide access to database to sales users.
- D. Create a chatter group and upload all Excel files to the group.
Answer: B
Explanation:
According to Trailhead, one of the best practices to increase Salesforce adoption is to migrate existing data from legacy systems or spreadsheets into Salesforce, so that users can access all their data in one place and leverage the features and functionality of Salesforce. Option B is the correct answer because it suggests defining a standard mapping and training sales users to import opportunity data from Excel files into Salesforce, which can help them transition from their old process and increase their confidence and satisfaction with Salesforce.
NEW QUESTION # 257
Universal Container has a Sales Cloud implementation for a sales team and an enterprise resource planning (ERP) as a customer master Sales team are complaining about duplicate account and data quality issues with account data. Which two solutions should a data architect recommend to resolve the complaints?
- A. Build a nightly sync job from ERP to Salesforce.
- B. Build a nightly batch job to de-dupe data, and merge account records.
- C. Integrate Salesforce with ERP, and make ERP as system of truth.
- D. Implement a de-dupe solution and establish account ownership in Salesforce
Answer: C,D
Explanation:
Integrating Salesforce with ERP and making ERP the system of truth (option B) and implementing a de-dupe solution and establishing account ownership in Salesforce (option D) are the two solutions that a data architect should recommend to resolve the complaints. Option B ensures that account data is consistent and accurate across both systems, while option D prevents duplicate records and clarifies who owns each account in Salesforce.
NEW QUESTION # 258
UC developers have created a new lightning component that uses an Apex controller using a SOQL query to populate a custom list view. Users are complaining that the component often fails to load and returns a time-out error. What tool should a data architect use to identify why the query is taking too long?
- A. Open a ticket with salesforce support to retrieve transaction logs to e analyzed for processing time.
- B. Use Splunk to query the system logs looking for transaction time and CPU usage.
- C. Enable and use the query plan tool in the developer console.
- D. Use salesforce's query optimizer to analyze the query in the developer console.
Answer: C
Explanation:
According to the Salesforce documentation, the query plan tool is a tool that can be enabled and used in the developer console to analyze the performance of a SOQL query. The query plan tool shows the cost, cardinality, sObject type, and relative cost of each query plan that Salesforce considers for a query. The relative cost indicates how expensive a query plan is compared to the Force.com query optimizer threshold. A query plan with a relative cost above 1.0 is likely to cause a time-out error.
To identify why the query is taking too long, a data architect should use the query plan tool in the developer console (option B). This way, the data architect can see which query plan is chosen by Salesforce and how it affects the performance of the query. The data architect can also use the query plan tool to optimize the query by adding indexes, filters, or limits to reduce the cost and improve the efficiency of the query.
NEW QUESTION # 259
Universal Containers uses Apex jobs to create leads in Salesforce. The business team has requested that lead creation failures should be reported to them. Which option does Apex provide to report errors from this Apex job?
- A. Save Apex errors in a custom object, and allow access to this object for reporting.
- B. Use Custom Object to store leads, and allow unprocessed leads to be reported.
- C. Use Apex services to email failures to business when error occurs.
- D. Use AppExchange package to clean lead information before Apex job processes them.
Answer: C
Explanation:
Saving Apex errors in a custom object can be a way to report errors from an Apex job. The article provides an example of how to create a custom object called AsyncApexError__c and use a trigger to insert error records into it. The custom object can then be used for reporting or notification purposes.
NEW QUESTION # 260
......
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