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Learn how to create visualizations of Microsoft Dynamics 365 Customer Service data. Prepare for MB-230.

Units in this learning path:

• 1 Introduction
• 2 Charts
• 3 Dashboards
• Historical Analytics
• 5 Power Bi
• 6 Check
• 7 Summary

Products: Dynamics 365, Dynamics Customer Service

Roles: Business User, Functional Consultant

Level: Intermediate

Subjects: Data Visualization

Duration: 51 minutes

Tune the indexing policy based on your SQL queries in Azure Cosmos DB for NoSQL.

Units in this learning path:

• Introduction
• Index Usage
• Review Read Heavy Index Patterns
• Review Write Heavy Index Patterns
• Exercise Optimize Containers Index Policy for Common Operations
• Knowledge Check
• Summary

Products: Azure Cosmos Db

Roles: Developer

Level: Intermediate

Subjects: Databases

Duration: 43 minutes

Customize indexes in Azure Cosmos DB for NoSQL

Units in this learning path:

• Introduction
• Customize Indexing Policy
• Evaluate Composite Indexes
• Exercise Configure Containers Index Policy Portal
• Knowledge Check
• Summary

Products: Azure Cosmos Db

Roles: Developer

Level: Intermediate

Subjects: Databases

Duration: 40 minutes

Microsoft Graph Toolkit components are flexible for customization. You can change the presentation of Microsoft Graph Toolkit components by using templates and learn troubleshooting techniques for rendering.

Units in this learning path:

• 1 Introduction
• 2 Change Presentation Using Templates
• 3 Exercise Change Presentation Using Templates
• 4 Troubleshoot Rendering
• 5 Exercise Troubleshoot Rendering
• 6 Summary

Products: M365, Ms Graph

Roles: Developer

Level: Beginner

Subjects: Data Visualization, Custom App Development

Duration: 20 minutes

Discover the differences between views and forms, and learn how to modify table views and forms effectively.

Units in this learning path:

• 1 Introduction
• 2 Exercise Modify Table Views
• 3 Modify Table Forms
• 4 Exercise Modify Table Forms
• 5 Check
• 6 Summary

Products: Power Apps, Dataverse, Office Excel

Roles: Maker

Level: Beginner

Subjects: Data Modeling, Custom App Development

Duration: 28 minutes

This credential earner has the advanced skills to analyze a data set to uncover actionable insights. The individual has the technical knowledge and practical skills to analyze and manipulate a data set, evaluate data to identify trends, evaluate the suitability of data analysis techniques, model probability distributions, apply data mining techniques, analyze data, select a machine learning algorithm, and interpret results of a data analysis. The earner has practiced essential workplace skills.

A Learning Plan pulls together training content for a particular role or solution, and organizes those assets from foundational to advanced. Use Learning Plans as a starting point to discover training that matters to you. This Learning Plan is…

A Learning Plan pulls together training content for a particular role or solution, and organizes those assets from foundational to advanced. Use Learning Plans as a starting point to discover training that matters to you. This Learning Plan is…

This credential earner understands basic statistical concepts such as measures of central tendency, dispersion, and linear regressions. The individual uses spreadsheets and database engines to handle, clean, and analyze data, and generates visual reports using data visualization tools such as Microsoft Power BI.

This credential earner has applied technical competencies of data analytics concepts for machine learning such as data processing, supervised learning, and unsupervised learning. The individual has the technical knowledge and practical skills on data collection and preprocessing; training and testing data, and uncovering data patterns and structures to predict outcomes and make decisions.

This credential earner has applied knowledge of sustainability concepts such as environmental, social, and governance (ESG) reporting, conservation, and resource management and uses data to gain insights about sustainability issues. The individual has skills in Python programming for data analysis and visualization, and proposal writing. The earner is aware of the job outlook, grant opportunities in sustainability fields, and the skills required for success in roles in the domain.

This credential earner has the advanced competencies to analyze data based on its source and type. The individual has the technical knowledge and practical skills to analyze the characteristics of data sets and sources and to refine data sets to align with organizational requirements. The earner has practiced essential workplace skills and explored data analytics career pathways.