MB-260 Microsoft Customer Insights Data Specialty (MB-260) Active Learning (English)

Volg de Microsoft Customer Data Platform Specialist training bij Master IT. Leer oplossingen implementeren die inzicht geven in klantprofielen, betrokkenheidsactiviteiten volgen om de klantervaringen te verbeteren en het klantenbehoud te vergroten. Na afronding van deze training kun je onder andere:

• Customer Insights-oplossingen ontwerpen en beheren
• Klantprofielen aanmaken door het verenigen van data
• AI-voorspellingen implementeren in Customer Insights

Deze training bevat Engelstalig lesmateriaal en wordt gegeven door een Nederlandssprekende docent (indien gewenst ook mogelijk in het Engels).

If your specialty is implementing solutions that provide insight into customer profiles and that track engagement activities to help improve customer experiences and increase customer retention, this certification could validate your skills and help open career doors.

Lesmethode

Bij Master IT train je met onze unieke lesmethode Active Learning, hiermee leer je aantoonbaar effectiever!

Wij zjn er namelijk van overtuigd dat je slimmer en met meer plezier leert als je actief met je lesstof omgaat. Onze klassen zijn gevuld met maximaal 8 cursisten. Hierbij luister je niet passief naar een trainer, maar ga je interactief en 1-op-1 met de trainer aan de slag om ervoor te zorgen dat jouw leerdoelen behaald worden. De theorie maak je je zoveel mogelijk zelf eigen, de nadruk van de begeleiding ligt op het begrijpen en toepassen van die theorie in de praktijk. Zo leer je alleen datgene wat je echt nodig hebt.

• Je bepaalt zelf je leertempo.
• De trainer coacht je bij het definiëren van jouw leertraject.
• Je onthoudt en begrijpt je nieuwe kennis beter.
• Alles draait om toepassing van de stof in jouw praktijk.

Om alle beschikbare trainingsdata in te zien, bekijk dan onze eigen website

Doelgroep

Most suited for one of the following job roles: Data Engineer, Data Analyst, Data Scientist, Functional ConsultantMost suited for one of the following job roles: Data Engineer, Data Analyst, Data Scientist, Functional Consultant

Voorkennis

As a candidate for this certification, you should have firsthand experience with Dynamics 365 Customer Insights, Power Query, Microsoft Dataverse, Common Data Model, Microsoft Power Platform and one or more additional Dynamics 365 apps. In addition, you need direct experience with practices related to privacy, compliance, consent, security, responsible AI, and data retention policy.

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

As a candidate for this certification, you should have firsthand experience with Dynamics 365 Customer Insights, Power Query, Microsoft Dataverse, Common Data Model, Microsoft Power Platform and one or more additional Dynamics 365 apps. In addition, you need direct experience with practices related to privacy, compliance, consent, security, responsible AI, and data retention policy.

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

Onderdelen

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

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

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

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

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

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