As I’m waiting for the MB-220 Customer Insights Journey certification to change, I wanted to do a series on the MB-260 Customer Insights Data certification. I’ll update this post with links to each section.
You should always start reading the study guide for the exam, you can find it here:
https://learn.microsoft.com/en-gb/credentials/certifications/resources/study-guides/mb-260
You should also go through the learning material on the exam page:
https://learn.microsoft.com/en-us/credentials/certifications/exams/mb-260/
The topics on this exam and the topics in the blog are:
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
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
Implement AI predictions in Customer Insights – Data (5–10%)
Use Copilot in Customer Insights – Data
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
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
As it’s a lot of content to write, I know it’ll take a long time to finish all of it, and it might change before I’m finished, but I’ll try to finish as fast as possible, if it takes too long, feel free to poke me, I work best under pressure!
Malin Martnes 