MB-260

Product Description

Introduce Microsoft MB-260 Exam

The Microsoft Dynamics 365 Customer Insights (Data) Specialist MB-260 exam is part of the Microsoft Certified: Customer Data Platform Specialty certification requirements. Candidates for the MB-260 exam implement solutions that provide insights into customer profiles and track engagement activities to help improve customer experiences and increase customer retention. The Microsoft MB-260 exam is available in multiple languages, including English, Japanese, Chinese (Simplified), German, French, Spanish, Portuguese (Brazil), and Italian. Ensure you can pass the MB-260 exam and earn the Microsoft Certified: Customer Data Platform Specialty certification to promote your positions.

Learning MB-260 Exam Objectives Is Strongly Recommended

• Describe Customer Insights components, including entities, relationships, activities, measures, and segments
• Describe support for near real-time updates
• Describe support for enrichment
• Describe the differences between individual profiles or business accounts.
• Describe use cases for Customer Insights
• Describe use cases for extending Customer Insights by using Microsoft Power Platform components
• Describe use cases for Customer Insights APIs
• Describe use cases for working with business accounts
• Determine which data sources to use
• Determine whether to use the managed data lake or an organization’s data lake
• Attach to a Microsoft Dataverse data lake
• Attach to Azure Data Lake Storage
• Ingest and transform data using Power Query connectors
• Attach to Azure Synapse Analytics
• Describe real-time ingestion capabilities and limitations
• Describe benefits of pre-unification data enrichment
• Ingest and update data in real-time
• Select tables and columns
• Resolve data inconsistencies, unexpected or null values, and data quality issues
• Evaluate and transform column data types
• Apply data shape transformations to tables
• Identify data sources that support incremental updates
• Configure incremental refresh
• Identify capabilities and limitations for scheduled refreshes
• Configure scheduled refreshes and on-demand refreshes
• Select Customer Insights entities and attributes for unification
• Select attribute types
• Select the primary key
• Deduplicate enriched entities
• Define deduplication rules
• Review deduplication results
• Specify a match order for entities
• Define match rules
• Define exceptions
• Include enriched entities in matching
• Configure normalization options
• Differentiate between basic and custom precision methods
• Specify the order of fields for merged tables
• Combine fields into a merged field
• Combine a group of fields
• Separate fields from a merged field
• Exclude fields from a merge
• Change the order of fields
• Rename fields
• Configure customer ID generation
• Group profiles into Clusters
• Review and create customer profiles
• View the results of data unification
• Verify output entities from data unification
• Update the unification settings
• Define which fields should be searchable
• Define filter options for fields
• Define indexes
• Create and manage relationships
• Create activities by using a new or existing relationship
• Create activities in real-time
• Manage activities
• Combine customer profiles with activity data from unknown users
• Configure and evaluate the customer churn models, including the transactional churn and subscription churn models
• Configure and evaluate the product recommendation model
• Configure and evaluate the customer lifetime value model
• Create a customer segment based on prediction model
• Configure and manage sentiment analysis
• Describe prerequisites for using custom Azure Machine Learning models in Customer Insights
• Implement workflows that consume machine learning models
• Manage workflows for custom machine learning models
• Create and manage tags
• Describe the different types of measures
• Create a measure
• Create a measure by using a template
• Configure measure calculations
• Modify dimensions
• Create and manage tags
• Describe methods for creating segments, including segment builder and quick segments
• Create a segment from customer profiles, measures, or AI predictions
• Create a segment based on a prediction model
• Find similar customers
• Project attributes
• Track usage of segments
• Export segments
• Describe how the system suggests segments for use
• Create a segment from a suggestion
• Create a suggested segment based on activity
• Configure refreshes for suggestions
• Configure overlap segments
• Configure differentiated segments
• Analyze insights
• Find similar segments with AI
• Configure a connection for exporting data
• Create a data export
• Define types of exports
• Configure on demand and scheduled data exports
• Define the limitations of segment exports
• Identify prerequisites for exporting data from Customer Insights
• Create connections between Customer Insights and Dynamics 365 apps
• Define which segments to export
• Export a Customer Insights segment into Dynamics 365 Marketing as a marketing segment
• Use Customer Insights profiles and segments with real-time marketing
• Export a Customer Insights profile into Dynamics 365 Marketing for customer journey orchestration
• Export a Customer Insights segment into Dynamics 365 Sales as a marketing list
• Identify Customer Insights data that can be displayed within Dynamics 365 apps
• Configure the Customer Card add-in for Dynamics 365 apps
• Identify permissions required to implement the Customer Card Add-in for Dynamics 365 apps
• Enrich customer profiles
• Configure and manage enrichments
• Enrich data sources before unification
• View enrichment results
• Add Consent Data to Customer Insights
• Use Consent Data
• Identify who can create environments
• Differentiate between trial and production environments
• Connect Customer Insights to Microsoft Dataverse
• Connect Customer Insights with Azure Data Lake Storage Account
• Manage existing environments
• Change or claim ownership of the environment
• Reset an existing environment
• Configure user permissions
• Describe available user permissions
• Differentiate between system refreshes and data source refreshes
• Describe refresh policies
• Configure a system refresh schedule
• Monitor and troubleshoot refreshes
• Describe when connections are used
• Configure and manage connections

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