Microsoft MB-260 : Microsoft Customer Data Platform Specialist

  • Exam Code: MB-260
  • Exam Name: Microsoft Customer Data Platform Specialist
  • Updated: Jul 26, 2026
  • Q & A: 120 Questions and Answers

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This exam measures your ability to accomplish the following technical tasks: design Customer Insights solutions; ingest data into Customer Insights; create customer profiles by unifying data; implement artificial intelligence predictions in Customer Insights; configure measures and segments; configure third-party connections; and administer Customer Insights.

Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/mb-260

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Microsoft Customer Data Platform Specialist Exam Certification Details:

Exam Price$165 (USD)
Exam NameMicrosoft Certified - Customer Data Platform Specialty
Duration120 mins
Sample QuestionsMicrosoft Customer Data Platform Specialist Sample Questions
Number of Questions40-60
Exam CodeMB-260
Passing Score700 / 1000
Schedule ExamPearson VUE
Books / TrainingCourse MB-260T00: Microsoft Customer Data Platform Specialty

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Microsoft MB-260 Exam Syllabus Topics:

TopicDetails

Design Customer Insights solutions (5-10%)

Describe Customer Insights- describe audience insights components, including entities, relationships, activities, measures, and segments
- analyze Customer Insights data by using Azure Synapse Analytics
- describe the process for consuming engagement insights data in audience insights
- describe support for near real-time updates
- describe support for enrichment
Describe use cases for Customer Insights- describe use cases for audience insights
- differentiate between audience insights and engagement insights
- describe use cases for creating reports by using Customer Insights
- describe use cases for extending Customer Insights by using Microsoft Power Platform components
- describe use cases for Customer Insights APIs

Ingest data into Customer Insights (10-15%)

Connect to data sources- determine which data sources to use
- determine whether to use the managed data lake or an organization’s data lake
- connect to Microsoft Dataverse
- connect to Common Data Model folders
- ingest data from Azure Synapse Analytics
- ingest data by using Azure Data Factory pipelines
Transform, cleanse, and load data by using Power Query- 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
Configure incremental refreshes for data sources- identify data sources that support incremental updates
- identify capabilities and limitations for scheduled refreshes
- configure scheduled refreshes and on-demand refreshes
- trigger refreshes by using Power Automate or the Customer Insights API

Create customer profiles by unifying data (20-25%)

Implement mapping- select Customer Insights entities and attributes for matching
- select attribute types
Implement matching- specify a match order for entities
- define match rules
- configure normalization options
- differentiate between low, medium, high, exact, and custom precision methods
- configure deduplication
- run a match process and review results
Implement merges- specify the order of fields for merged tables
- combine fields into a merged field
- separate fields from a merged field
- exclude fields from a merge
- run a merge and review results
Configure search and filter indexes- define which fields should be searchable
- define filter options for fields
- define indexes
Configure relationships and activities- create and manage relationships
- create activities by using a new or existing relationship
- manage activities

Implement AI predictions in Customer Insights (10-15%)

Configure prediction models- 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
Implement machine learning models- 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

Configure measures and segments (15-20%)

Create and manage measures- describe the different types of measures
- create a measure
- create a measure by using a template
- configure measure calculations
- modify dimensions
Create segments- describe methods for creating segments, including blank segments
- create a segment from customer profiles, measures, or AI predictions
- find similar customers
Find suggested segments- describe how the system suggests segments for use
- create a segment from a suggestion
- configure refreshes for suggestions
Create segment insights- configure overlap segments
- configure differentiated segments
- analyze insights

Configure third-party connections (10-15%)

Configure connections and exports- configure a connection for exporting data
- create a data export
- schedule a data export
Export data to Dynamics 365 Marketing or Dynamics 365 Sales- 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
- 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
Display Customer Insights data from within Dynamics 365 apps- 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

Administer Customer Insights (5-10%)

Create and configure environments- identify who can create environments
- differentiate trial and production environments
- manage existing environments
- describe available roles
- configure user permissions and guest user permissions
Manage system refreshes- differentiate between system refreshes and data source refreshes
- describe refresh policies
- configure a system refresh schedule
- monitor and troubleshoot refreshes

Microsoft MB-260 Exam Syllabus Topics:

SectionObjectives
Create unified customer profiles- Match and merge customer data
- Define identity resolution rules
Activate and integrate data- Configure integrations with Dynamics 365 and external systems
- Export data to downstream applications
Configure Microsoft Dynamics 365 Customer Insights (Data)- Set up and configure Customer Insights environment
- Configure data sources and connections
Ingest and transform data- Transform and prepare data for unification
- Connect and ingest data from multiple sources
Enrich and analyze customer data- Apply enrichment sources
- Generate insights and segments
Manage, monitor, and secure Customer Insights- Monitor system health and performance
- Configure security and compliance settings

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