Classes Data & Analytics
DP-600T00 Microsoft Technical Partner Delivered
DP-600T00 Implement analytics solutions using Microsoft Fabric
- 4 days
- 1 upcoming date
- 1 guaranteed to run
- May qualify for CEU/PDU credit
Upcoming dates
All times shown in the class's own timezone. 1 of 1 are guaranteed to run, meaning they go ahead regardless of enrollment.
| Dates | Starts | Where | Status | Seat | Book |
|---|---|---|---|---|---|
| Nov 17-20 | 9:00 AM to 5:00 PM EST | Live virtual | GUARANTEED | $2,495 |
About this class
We have 1 scheduled date of DP-600T00 Implement analytics solutions using Microsoft Fabric, starting Nov 17-20. It is guaranteed to run regardless of enrollment. Seats are $2,495 each over 4 days, courseware included. Book online with a card, or send a purchase order and we will invoice on net 30 terms.
This course covers how to prepare, enrich, and serve data for analysis by consumers such as data analysts, report developers, and AI agents. The course focuses on designing dimensional models and transforming data by using dataflows, notebooks, and T-SQL across lakehouses, warehouses, and eventhouses in Microsoft Fabric. The course also covers building and optimizing semantic models, managing the analytics development lifecycle, and enforcing security and governance across data assets.
Course outline
1 - Introduction to end-to-end analytics using Microsoft Fabric
- Explore end-to-end analytics with Microsoft Fabric
- Explore data teams and Microsoft Fabric
- Enable and use Microsoft Fabric
- Module assessment
2 - Discover and connect to data in OneLake
- Understand OneLake
- Browse and connect to data in OneLake
- Discover streaming data in Real-Time hub
3 - Get started with lakehouses in Microsoft Fabric
- Describe lakehouse features and capabilities
- Ingest and transform data in a lakehouse
- Query and analyze lakehouse data
- Module assessment
4 - Get started with data warehouses in Microsoft Fabric
- Understand data warehouses
- Understand data warehouses in Fabric
- Query and transform data
- Model data in a warehouse
- Secure and monitor a warehouse
- Module assessment
5 - Get started with Real-Time Intelligence in Microsoft Fabric
- What is real-time data analytics?
- Real-Time Intelligence in Microsoft Fabric
- Ingest and transform real-time data
- Store and query real-time data
- Visualize real-time data
- Automate actions
- Module assessment
6 - Choose data stores in Microsoft Fabric
- Describe analytical data store options
- Evaluate lakehouse capabilities
- Evaluate warehouse capabilities
- Evaluate eventhouse capabilities
- Case study - Choose data stores for an integrated analytics solution
- Module assessment
7 - Design dimensional models for analytics in Microsoft Fabric
- Describe dimensional schema types
- Design fact tables
- Design dimension tables
- Implement slowly changing dimensions
8 - Transform data using Dataflows Gen2 in Microsoft Fabric
- Understand Dataflows Gen2
- Transform data with Power Query
- Optimize Dataflows Gen2 performance
9 - Transform data using notebooks in Microsoft Fabric
- Describe notebooks in Fabric
- Shape and clean data
- Combine and aggregate data
- Write and size Delta tables
10 - Transform data using T-SQL in Microsoft Fabric
- Transform data with T-SQL queries
- Create views for reusable logic
- Build stored procedures
- Implement dimensional tables
11 - Create DAX calculations in semantic models
- Create calculated tables
- Create calculated columns
- Understand implicit measures
- Create explicit measures
- Use iterator functions
12 - Design semantic models for scale in Microsoft Fabric
- Choose a storage mode
- Design star schema for semantic models
- Design scalable calculations
- Configure settings for scale
- Module assessment
13 - Optimize semantic model performance
- Use Performance analyzer to diagnose issues
- Optimize DAX calculations
- Reduce cardinality for better performance
- Implement aggregations
- Troubleshoot common performance issues
14 - Enforce semantic model security
- Implement row-level security
- Apply object-level security
- Test security and manage roles
- Module assessment
15 - Manage the semantic model development lifecycle
- Create reusable Power BI assets
- Manage Power BI content in version control
- Manage semantic models with the XMLA endpoint
- Deploy content through stages
- Maintain and monitor semantic models
- Module assessment
16 - Prepare the semantic layer for AI in Microsoft Fabric
- Understand what AI needs from your data
- Design gold layers with AI in mind
- Prepare a semantic model for AI
- From semantic models to enterprise ontology
- Validate AI readiness
- Module assessment
17 - Understand Microsoft Fabric IQ fundamentals
- Get started with Fabric IQ
- Explore Microsoft Fabric IQ components
- Understand the ontology modeling paradigm
- Module assessment
18 - Create an ontology with Fabric IQ
- Choose an ontology creation approach
- Build an ontology manually
- Generate an ontology from a Power BI semantic model
- Connect an ontology to data
- Configure ontology relationships
- Preview the ontology
- Module assessment
19 - Secure data access in Microsoft Fabric
- Understand the Fabric security model
- Configure workspace and item permissions
- Apply granular permissions
- Module assessment
20 - Secure a Microsoft Fabric data warehouse
- Explore dynamic data masking
- Implement row-level security
- Implement column-level security
- Configure SQL granular permissions using T-SQL
- Module assessment
21 - Govern data in Microsoft Fabric with Purview
- Govern data in Microsoft Fabric
- Why use Microsoft Purview with Microsoft Fabric?
- Govern data in the Microsoft Purview hub
- Module assessment
22 - Govern analytics data in Microsoft Fabric
- Classify and protect data in Microsoft Fabric
- Endorse and document data assets
- Govern data for AI consumption
Before you attend
- PL-300 certification or equivalent Power BI expertise
- Experience with SQL, KQL, or DAX
- Familiarity with enterprise-level data modeling, transformation, and deployment
Who this is for
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.
How reserving works. Your card is authorized, not charged. We confirm the seat with the training center, usually within one business day, and take payment only once it is held. If the class turns out to be full we release the authorization and you are not charged.
Request a quote
Tell us how many people and roughly when. We'll come back with dates, seat price, and a total by the end of the next business day.