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Implement analytics solutions using Microsoft Fabric
Duration
4
Course
MOC-DP-600T00
Available Formats
Classroom Training, Online Training
Course Description
Overview
This course covers methods and practices for implementing and managing enterprise-scale data analytics solutions using Microsoft Fabric. Students will build on existing analytics experience and will learn how to use Microsoft Fabric components, including lakehouses, data warehouses, notebooks, dataflows, data pipelines, and semantic models, to create and deploy analytics assets.This course is best suited for those who have the PL-300 certification or similar expertise in using Power BI for data transformation, modeling, visualization, and sharing. Also, learners should have prior experience in building and deploying data analytics solutions at the enterprise level.
Objectives
By the end of this course, you're able to:
- Evaluate lakehouse, warehouse, and eventhouse capabilities and confidently choose the appropriate data store for a given business scenario.
- Learn why and how to create each of DAX Calculated tables, Calculated columns and Measures.
- Prepare semantic models and data structures so that Copilot, data agents, and other AI tools deliver accurate, business-relevant insights.
- Configure the right level of access for each user, from workspace roles to OneLake security roles, following the principle of least privilege.
Audience
This course is intended for data professionals with experience in data modeling, transformation, and analytics. Learners should have prior experience translating business requirements into analytical measures by using Structured Query Language (SQL) or Data Analysis Expressions (DAX). Experience building semantic models and reports in Power BI is recommended. Familiarity with Kusto Query Language (KQL) and Python is also helpful but not required.
Prerequisites
- Experience working with data stores such as lakehouses or warehouses
- Familiarity with SQL query syntax
- Understanding of data modeling concepts such as tables, relationships, and keys
- Experience building reports in Power BI
- Familiarity with DAX syntax including measures and calculated columns
- Understanding of dimensional data modeling design concepts
- Experience designing and publishing semantic models in Microsoft Fabric
- Familiarity with DAX measures and relationships in semantic models
- Basic understanding of how AI agents consume structured data
- Experience administering Microsoft Fabric workspaces
- Familiarity with role-based access control concepts
- Understanding of data sensitivity classification and labeling
Topics
Explore analytics data stores in Microsoft Fabric
- Introduction to end-to-end analytics using Microsoft Fabric
- Discover and connect to data in OneLake
- Get started with lakehouses in Microsoft Fabric
- Get started with data warehouses in Microsoft Fabric
- Get started with Real-Time Intelligence in Microsoft Fabric
- Choose data stores in Microsoft Fabric
- Design dimensional models for analytics in Microsoft Fabric
- Transform data using Dataflows Gen2 in Microsoft Fabric
- Transform data using notebooks in Microsoft Fabric
- Transform data using T-SQL in Microsoft Fabric
- Create DAX calculations in semantic models
- Design semantic models for scale in Microsoft Fabric
- Optimize semantic model performance
- Enforce semantic model security
- Manage the semantic model development lifecycle
- Prepare the semantic layer for AI in Microsoft Fabric
- Understand Microsoft Fabric IQ fundamentals
- Create an ontology with Fabric IQ
- Secure data access in Microsoft Fabric
- Secure a Microsoft Fabric data warehouse
- Govern analytics data in Microsoft Fabric
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Learn at your own pace with anytime, anywhere training
- Same in-demand topics as instructor-led public and private classes.
- Standalone learning or supplemental reinforcement.
- e-Learning content varies by course and technology.
- View the Self-Paced version of this outline and what is included in the SPVC course.
- Learn more about e-Learning
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title
Please take a moment to fill out this form. We will get back to you as soon as possible.
All fields marked with an asterisk (*) are mandatory.