Study guide for Exam MB-260: Microsoft Dynamics 365 Customer Insights (Data) Specialist

Purpose of this document

This study guide should help you understand what to expect on the exam and includes a summary of the topics the exam might cover and links to additional resources. The information and materials in this document should help you focus your studies as you prepare for the exam.

Useful links	Description
Review the skills measured as of April 15, 2024	This list represents the skills measured AFTER the date provided. Study this list if you plan to take the exam AFTER that date.
Review the skills measured prior to April 15, 2024	Study this list of skills if you take your exam PRIOR to the date provided.
Change log	You can go directly to the change log if you want to see the changes that will be made on the date provided.
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Exam scoring and score reports	A score of 700 or greater is required to pass.
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Take a practice test	Are you ready to take the exam or do you need to study a bit more?

Updates to the exam

Our exams are updated periodically to reflect skills that are required to perform a role. We have included two versions of the Skills Measured objectives depending on when you are taking the exam.

We always update the English language version of the exam first. Some exams are localized into other languages, and those are updated approximately eight weeks after the English version is updated. While Microsoft makes every effort to update localized versions on this schedule, there may be times when localized versions of an exam are not updated on this schedule. Other available languages are listed in the Schedule Exam section of the Exam Details webpage. If the exam isn't available in your preferred language, you can request an additional 30 minutes to complete the exam.

Note

The bullets that follow each of the skills measured are intended to illustrate how we are assessing that skill. Related topics may be covered in the exam.

Note

Most questions cover features that are general availability (GA). The exam may contain questions on Preview features if those features are commonly used.

Skills measured as of April 15, 2024

Audience profile

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.

You should have firsthand experience with:

• Dynamics 365 Customer Insights - Data

• Microsoft Power Query

• Microsoft Dataverse

• Microsoft Azure Data Lake Storage

• Azure Data Factory pipelines

You should also have direct experience with practices related to:

• Privacy, compliance, and consent

• Security

• Responsible AI

As a candidate for this exam, you need experience with data processes related to:

• Preparation

• Matching

• Segmentation

• Enhancement

• Deduplication

You should have a general understanding of:

• Azure Machine Learning

• Azure Synapse Analytics

• Azure architecture

Skills at a glance

• Describe Dynamics 365 Customer Insights – Data (5–10%)

• Ingest data (10–15%)

• Create customer profiles through data unification (35–40%)

• Implement AI predictions (5–10%)

• Configure measures and segments (15–20%)

• Configure third-party connections (5–10%)

• Administer Customer Insights – Data (5–10%)

Describe Dynamics 365 Customer Insights - Data (5–10%)

Describe Customer Insights - Data functionality

• Describe Customer Insights - Data components

• Describe support for near real-time updates

• Describe the differences between individual consumer and business account profiles

• Describe support for Microsoft Fabric

• Describe the tables and relationships in Customer Insights - Data

• Describe real-time ingestion capabilities and limitations

• Describe benefits of pre-unification data enrichment

• Identify when to use the managed data lake or an organization’s own data lake

Describe use cases for Customer Insights - Data

• Describe use cases for Customer Insights - Data

• Describe use cases for Customer Insights - Data APIs

• Describe the integration between Customers Insights - Data and Customer Insights - Journeys

• Describe use cases for machine learning

Ingest data (10–15%)

Connect to data sources

• Attach to Microsoft Dataverse

• Attach to Azure Data Lake Storage

• Ingest and transform data by using Power Query

• Attach to Azure Synapse Analytics

• Update Unified Customer Profile fields in near real-time

• Troubleshoot common ingestion errors

• Attach to data stored in Delta Lake format

• Configure incremental refresh

Transform, cleanse, and load data

• Select tables and columns

• Resolve data inconsistencies, unexpected or null values, and data quality issues

• Evaluate and transform column data types

• Transform data from Dataverse

Create customer profiles through data unification (35–40%)

Select source fields

• Select Customer Insights tables and attributes for unification

• Describe attribute types

• Describe the requirements for a primary key

Remove duplicate records

• Deduplicate enriched tables

• Define deduplication rules, including exceptions, winner, and alternate records

• Manage merged preferences

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

• Configure custom match conditions

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

• Configure customer ID generation

• Describe B2B unification

Implement business data separation

• Describe 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 and manage activities

• Combine customer profiles with activity data from unknown users

• Describe how to use customer consent

• Describe how to use web data for personalization

• Describe relationship paths

• Set the B2B account relationship with contacts

Configure search and filter indexes

• Define which fields should be searchable

• Define filter options for fields

• Define indexed fields

Implement AI predictions (5–10%)

Configure built-in 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

• Configure and manage sentiment analysis

Implement machine learning models

• Describe prerequisites for using custom Azure Machine Learning models in Customer Insights - Data

• Create and manage workflows that consume machine learning models

• Describe prerequisites for using custom models from Azure Synapse Analytics in Customer Insights - Data

Configure measures and segments (15–20%)

Create and manage measures

• Create and manage tags

• Describe the different types of measures

• Create a measure

• Configure measure calculations

• Modify dimensions

• Schedule measures

Create and manage segments

• Describe methods for creating segments, including segment builder and quick segments

• Create a segment from customer profiles or measures

• Create a segment based on a prediction model

• Describe projected attributes

• Schedule segments

Find suggested segments

• Describe how the system suggests segments for use

• Create a suggested segment based on a measure

• Create a suggested segment based on activity

Create segment insights

• Configure overlap segments

• Configure differentiated segments

• Review the overlap or differentiator analysis

• Find similar customers by using AI

Configure third-party connections (5–10%)

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

Implement data enrichment

• Enrich customer profiles

• Configure and manage enrichments

• Enrich data sources before unification

Administer Customer Insights - Data (5–10%)

Create and configure environments

• Identify who can create environments

• Differentiate between trial, sandbox, and production environments

• Connect Customer Insights - Data to Dataverse

• Connect Customer Insights - Data with Azure Data Lake Storage Account

• Manage environments

• Assign user permissions

• Create an environment in Customer Insights - Data

• Manage keys in Azure key vault

Manage system refreshes

• Differentiate between system refreshes and data source refreshes

• Describe the system refresh process

• Configure a system refresh schedule

• Monitor and troubleshoot refreshes

Study resources

We recommend that you train and get hands-on experience before you take the exam. We offer self-study options and classroom training as well as links to documentation, community sites, and videos.

Study resources	Links to learning and documentation
Get trained	Choose from self-paced learning paths and modules or take an instructor-led course
Find documentation	Dynamics 365 documentation and learning modules Dynamics 365 Customer Insights documentation
Ask a question	Microsoft Q&A | Microsoft Docs
Get community support	Microsoft Dynamics Community
Follow Microsoft Learn	Microsoft Learn - Microsoft Tech Community

Change log

Key to understanding the table: The topic groups (also known as functional groups) are in bold typeface followed by the objectives within each group. The table is a comparison between the two versions of the exam skills measured and the third column describes the extent of the changes.

Skill area prior to April 15, 2024	Skill area as of April 15, 2024	Changes
Audience profile		Major
Design Dynamics 365 Customer Insights - Data solutions	Describe Dynamics 365 Customer Insights - Data	No % change
Describe Customer Insights - Data	Describe Customer Insights - Data functionality	Major
Describe use cases for Customer Insights - Data	Describe use cases for Customer Insights - Data	Major
Ingest data into Customer Insights - Data	Ingest data	No % change
Connect to data sources	Connect to data sources	Major
Transform, cleanse, and load data by using Power Query	Transform, cleanse, and load data	Minor
Configure incremental refreshes for data sources		Removed
Create customer profiles through data unification	Create customer profiles through data unification	% of exam increased
Select source fields	Select source fields	Minor
Remove duplicate records	Remove duplicate records	Minor
Match conditions	Match conditions	Minor
Unify customer fields	Unify customer fields	Major
Implement business data separation	Implement business data separation	Minor
Review data unification	Review data unification	No change
Configure relationships and activities	Configure relationships and activities	Major
Create a unified contact profile for B2B accounts		Removed
Configure search and filter indexes	Configure search and filter indexes	Minor
Implement AI predictions in Customer Insights - Data	Implement AI predictions	No % change
Use Copilot in Customer Insights - Data		Removed
Configure prediction models	Configure built-in prediction models	Minor
Implement machine learning models	Implement machine learning models	Major
Configure measures and segments	Configure measures and segments	% of exam increased
Create and manage measures	Create and manage measures	Minor
Create and manage segments	Create and manage segments	Major
Find suggested segments	Find suggested segments	Minor
Create segment insights	Create segment insights	Minor
Configure third-party connections	Configure third-party connections	% of exam decreased
Configure connections and exports	Configure connections and exports	No change
Export data to Dynamics 365 Customer Insights - Journeys or Dynamics 365 Sales		Removed
Display Customer Insights - Data data from within Dynamics 365 apps		Removed
Implement Data Enrichment	Implement data enrichment	Minor
Use Customer Consent data		Removed
Use Customer Insights data across Power Platform and M365 applications		Removed
Administer Customer Insights - Data	Administer Customer Insights - Data	No % change
Create and configure environments	Create and configure environments	Major
Manage system refreshes	Manage system refreshes	Minor
Create and manage connections		Removed

Skills measured prior to April 15, 2024

Audience profile

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

Skills at a glance

• Design Dynamics 365 Customer Insights - Data solutions (5–10%)

• Ingest data into Customer Insights - Data (10–15%)

• Create customer profiles through data unification (30–35%)

• Implement AI predictions in Customer Insights - Data (5–10%)

• Configure measures and segments (10–15%)

• Configure third-party connections (10–15%)

• Administer Customer Insights - Data (5–10%)

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