Description

Note: Currently the exam is available in beta version 

Candidates for this exam implement solutions that provide insights into customer profiles and that track engagement activities to help improve customer experiences and increase customer retention. 

Candidates should have firsthand experience with Dynamics 365 Customer Insights and one or more additional Dynamics 365 apps, Power Query, Microsoft Dataverse, Common Data Model, and Microsoft Power Platform. They should also have direct experience with practices related to privacy, compliance, consent, security, responsible AI, and data retention policy. 

Candidates need experience with processes related to KPIs, data retention, validation, visualization, preparation, matching, fragmentation, segmentation, and enhancement. They should have a general understanding of Azure Machine Learning, Azure Synapse Analytics, and Azure Data Factory. 

Course Fee: £2,499+VAT

Objectives

•  Design Customer Insights solutions 
• Ingest data into Customer Insights 
• Create customer profiles by unifying data
• Implement AI predictions in Customer Insights
• Configure measures and segments 
• Configure third-party connections  
• Administer Customer Insights 

Who Should Attend

Candidates for this exam implement solutions that provide insights into customer profiles and that track engagement activities to help improve customer experiences and increase customer retention. Candidates should have firsthand experience with Dynamics 365 Customer Insights and one or more additional Dynamics 365 apps, Power Query, Microsoft Dataverse, Common Data Model, and Microsoft Power Platform. They should also have direct experience with practices related to privacy, compliance, consent, security, responsible AI, and data retention policy. Candidates need experience with processes related to KPIs, data retention, validation, visualization, preparation, matching, fragmentation, segmentation, and enhancement. They should have a general understanding of Azure Machine Learning, Azure Synapse Analytics, and Azure Data Factory. 

Prerequisites

Candidates need experience with processes related to KPIs, data retention, validation, visualization, preparation, matching, fragmentation, segmentation, and enhancement. They should have a general understanding of Azure Machine Learning, Azure Synapse Analytics, and Azure Data Factory.

Course Outline

 Module 1: Design Customer Insights solutions  

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  

Module 2: Ingest data into Customer Insights  

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  

Module 3: Create customer profiles by unifying data  

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  

Module 4: Implement AI predictions in Customer Insights  

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  

Impute missing values by using predictions 

• describe processes for predicting missing values 
• implement the missing values feature  

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  

Module 5: Configure measures and segments 

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  

Module 6: Configure third-party connections 

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  

Module 7: Administer Customer Insights 

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 

About The Trainer

A Microsoft Dynamics Certified Trainer.

Course Fee

£2499+VAT