This exam measures your ability to accomplish the following technical tasks: design Dynamics 365 Customer Insights - Data solutions; ingest data into Customer Insights - Data; create customer profiles through data unification; implement AI predictions in Customer Insights - Data; configure measures and segments; configure third-party connections; and administer Customer Insights - Data.
As a candidate for this exam, you implement solutions that provide insights into customer profiles and that track engagement activities to help:
◉ Improve customer experiences.
◉ Increase customer retention.
You should have firsthand experience with:
◉ Dynamics 365 Customer Insights - Data and one or more additional Dynamics 365 apps
◉ Microsoft Power Query
◉ Microsoft Dataverse
◉ Common Data Model
◉ Microsoft Power Platform
You should also have direct experience with practices related to:
◉ Privacy
◉ Compliance
◉ Consent
◉ Security
◉ Responsible AI
◉ Data retention policy
As a candidate for this exam, you need experience with processes related to key performance indicators (KPIs), data retention, validation, visualization, preparation, matching, fragmentation, segmentation, and enhancement. You should have a general understanding of:
◉ Azure Machine Learning
◉ Azure Synapse Analytics
◉ Azure Data Factory
Microsoft Customer Insights Data Specialist Exam Summary:
| Exam Name | Microsoft Certified - Dynamics 365 Customer Insights Data Specialty |
| Exam Code | MB-260 |
| Exam Price | $165 (USD) |
| Exam Price | 120 mins |
| Number of Questions | 40-60 |
| Passing Score | 700 / 1000 |
| Books / Training | Course MB-260T00: Microsoft Customer Data Platform Specialty |
| Sample Questions | Microsoft Customer Insights Data Specialist Sample Questions |
| Practice Exam | Microsoft MB-260 Certification Practice Exam |
Microsoft MB-260 Exam Syllabus Topics:
| Topic | Details |
| Design Dynamics 365 Customer Insights - Data solutions (5-10%) | |
| Describe Customer Insights - Data | - Describe Dynamics 365 Customer Insights - Data components, including tables, relationships, enrichments, activities, measures, and segments - Describe the first run experience (FRE) in D365 Customer Insights - Data - Describe support for near real-time updates - Describe support for enrichment - Describe the differences between individual consumer and business account profiles |
| Describe use cases for Customer Insights - Data | - Describe use cases for Dynamics 365 Customer Insights - Data - Describe use cases for extending Customer Insights - Data by using Microsoft Power Platform components - Describe use cases for Customer Insights - Data APIs - Describe use cases for working with business accounts |
| Ingest data into Customer Insights - Data (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 - 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 data in real-time - Update Unified Customer Profile fields in real-time - Understand common ingestion errors |
| 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 |
| Configure incremental refreshes for data sources | - Identify data sources that support incremental updates - Configure incremental refresh - Identify capabilities and limitations for scheduled refreshes - Configure scheduled refreshes and on-demand refreshes |
| Create customer profiles through data unification (30-35%) | |
| Select source fields | - Select Customer Insights tables and attributes for unification - Select attribute types - Select the primary key |
| Remove duplicate records | - Deduplicate enriched tables - Define deduplication rules - Review deduplication results |
| Match conditions | - Specify a match order for tables - Define match rules - Define exceptions - Include enriched tables in matching - Configure normalization options - Differentiate between basic and custom precision methods |
| Unify customer fields | - 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 - Group profiles into Clusters |
| Implement business data separation | - Understand business unit separation prerequisites - Access business data in Dataverse - Implement Customer Insights - Data business unit integrations |
| Review data unification | - Review and create customer profiles - View the results of data unification - Verify output tables from data unification - Update the unification settings |
| Configure relationships and activities | - 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 - Display Customer Insights - Data Activities in D365 Activity Timeline |
| Create a unified contact profile for B2B accounts | - Create unified contact profile - Set the relationship between contacts and accounts - Define the semantic fields - Review contact unification - Verify output tables from data unification |
| Configure search and filter indexes | - Define which fields should be searchable - Define filter options for fields - Define indexes |
| Implement AI predictions in Customer Insights - Data (5-10%) | |
| Use Copilot in Customer Insights - Data | - Understand key Discovery page components |
| 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 - Create a customer segment based on prediction model - Configure and manage sentiment analysis |
| Implement machine learning models | - Describe prerequisites for using custom Azure Machine Learning models in Customer Insights - Data - Use a wizard to bring custom prediction models to Customer Insights - Data - Implement workflows that consume machine learning models - Manage workflows for custom machine learning models |
| Configure measures and segments (10-15%) | |
| Create and manage measures | - 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 - Schedule Measures |
| Create and manage segments | - 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 |
| Find suggested 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 |
| Create segment insights | - Configure overlap segments - Configure differentiated segments - Analyze insights - Find similar segments with AI |
| Configure third-party connections (10-15%) | |
| Configure connections and exports | - 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 |
| Export data to Dynamics 365 Customer Insights – Journeys or Dynamics 365 Sales | - Identify prerequisites for exporting data from Dynamics 365 Customer Insights - Data - Create connections between Dynamics 365 Customer Insights - Data and Dynamics 365 apps - Define which segments to export - Export a Dynamics 365 Customer Insights - Data segment into Dynamics 365 Customer Insights - Journeys as a marketing segment - Use Dynamics 365 Customer Insights - Data profiles and segments with real-time marketing - Export a Dynamics 365 Customer Insights - Data profile into Dynamics 365 Customer Insights - Journeys for customer journey orchestration - Export a Dynamics 365 Customer Insights - Data segment into Dynamics 365 Sales as a marketing list - Display Customer Insights - Data data from within Dynamics 365 apps Identify what data from Dynamics 365 Customer Insights - Data 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 |
| Implement Data Enrichment | - Enrich customer profiles - Configure and manage enrichments - Enrich data sources before unification - View enrichment results |
| Use Customer Consent data | - Add Consent Data to Customer Insights - Data - Use Consent Data |
| Use Customer Insights - Data data across Power Platform and M365 applications | - Use D365 Customer Insights - Data chatbot for Microsoft Teams - Connect Power Apps and Dynamics 365 Customer Insights - Data - Use the Power Automate Connector for Dynamics 365 Customer Insights - Data - Configure the Dynamics 365 Customer Insights connector for Power BI - Data |
| Administer Customer Insights - Data (5-10%) | |
| Create and configure environments | - Identify who can create environments - Differentiate between trial and production environments - Connect Customer Insights - Data to Microsoft Dataverse - Connect Customer Insights - Data with Azure Data Lake Storage Account Manage existing environments - Change or claim ownership of the environment - Reset an existing environment - Delete an existing environment - Configure user permissions - Describe available user permissions - Export diagnostic logs |
| Manage system refreshes | - Differentiate between system refreshes and data source refreshes - Describe refresh policies - Configure a system refresh schedule - Monitor and troubleshoot refreshes |
| Create and manage connections | - Describe when connections are used - Configure and manage connections |
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