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| Topic | Details |
|---|---|
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 |
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MB-260 Dumps cover the Microsoft MB-260 Certification Exam:
Ingest data into Customer Insights: 15%
Implement AI predictions in Customer Insights: 15%
Design Customer Insights solutions: 10%
Configure third-party connections: 15%
Administer Customer Insights: 10%
Configure measures and segments: 15%
Create customer profiles by unifying data: 20%
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/mb-260
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In India: 50,000 INR
In the UK: 80,000 GBP
In the United States: 65,000 USD
In Singapore: 60,000 SGD
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