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  3. Master Course in Microsoft MB-260 (Customer Data Platform)
Master Course in Microsoft MB-260 (Customer Data Platform) course thumbnail
IT & Software

1 February, 2024

Microsoft MB-260, Customer Data Platform Specialty, Dynamics 365, Microsoft Dataverse, Machine learning models

Free with coupon

Master Course in Microsoft MB-260 (Customer Data Platform)

Master Course in Microsoft MB-260 - Customer Data Platform Specialty

An online and offline customer data platform combines disparate online and offline data sources to create a single view of your customers.

It can validate your skills and help open career doors if you specialize in building solutions that provide insight into customer profiles, track engagement activities, and improve customer experiences.

Customer data platforms (CDPs) are used for marketing. You can build a single, coherent, complete view of your customers by collecting and combining first-party data from multiple sources. Then, marketers can use it to create targeted, personalized campaigns.

CDPs (customer data platforms) have these key features:

Ingestion of data.

Resolution of identity issues.

Processing data.

Segmentation in real-time.

Synchronization and syndication of data.

Who uses a CDP the most?

Although sales, demand generation, and other go-to-market teams will ultimately benefit from a CDP, these jobs are often the ones working on it and managing it after it's implemented:

· The marketing department

· Operational aspects of sales

· Operational growth

· Marketing growth

· Operations with data

· Data engineer

Here are the five major topics I'd like to cover in this master's course:

1. Use Dynamics 365 Customer Insights to identify your audience and consume it

2. Data sources imported with Power Query, data cleaned, transformed, and loaded, Microsoft Dataverse data sets

3. Establish a unified profile for customers by setting up duplicate records, matching conditions, and source fields

4. Configurable indexes, relationships and activities, Measures and Segmentation

5. Utilize machine-learning models to enrich data, enhance brands and interests, and predict subscription churn


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