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Exam DP-600 Implementing Analytics Solutions Using Microsoft Fabric (Video)

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Exam DP-600 Implementing Analytics Solutions Using Microsoft Fabric (Video)

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  • List Price: $199.99
  • Estimated Release: Jul 25, 2025
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Description

  • Copyright 2024
  • Edition: 1st
  • Online Video
  • ISBN-10: 0-13-836182-7
  • ISBN-13: 978-0-13-836182-2

Master how to use Microsoft Fabric to plan, implement, and manage data analytics solutions

  • Comprehensive, hands-on coverage of Microsoft Fabric: Learn to design, create, and manage end-to-end analytics solutions with Microsoft Fabric.
  • Real-world labs and scenarios mapped to exam skills: Reinforce your learning with targeted labs directly mapped to DP-600 objectives, covering semantic models, Power BI reporting, Medallion architecture, and workspace management.
  • Get exam-ready for DP-600: Align your learning with Microsofts official exam objectives and gain hands-on skills to succeed as a Fabric Analytics Engineer.
  • Expert guidance from a Microsoft Certified Trainer: Benefit from expert instruction by Akriti Lal, a leading Microsoft Fabric trainer, providing practical tips and insights for mastering every core exam topic.

The Microsoft Exam DP-600: Implementing Analytics Solutions Using Microsoft Fabric is designed to test your expertise in designing, creating, and managing analytical assets using Microsoft Fabric. Throughout the course, Microsoft Certified Trainer and Microsoft Fabric expert Akriti Lai takes you through everything you need to know on the DP-600 exam. Through targeted labs and discussion, you gain an understanding of topics such as Fabric and SQL fundamentals, data ingestion and preparation, medallion architecture in Microsoft Fabric, Power BI, and how to design and build semantic models. Get ready to take on the DP-600 exam with confidence!

Skill Level:

Intermediate

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Sample Content

Table of Contents

Lesson 1: Introduction to Data Analytics Solutions using Microsoft Fabrics
1.1 Introduction to Data Analysis & Microsoft Fabric
1.2 Introduction to Microsoft Fabric components
1.3 Understanding the role of Lakehouse, Data Warehouses, Notebooks, Dataflows, Data Pipelines, Semantic Models, and Reports 
1.4 Understanding Fabric admin task, How to manage admin center and Managing user access
Lesson 2: Data Warehousing and SQL Fundamentals
2.1 Understanding relational databases and Understanding SQL fundamentals
2.2 Designing and implementing Datawarehouse in Microsoft Fabric
2.3 ETL data into the Microsoft Fabric data warehouse
2.4 Load data using Data Pipeline, Dataflow Gen2 & T-SQL
2.5 Monitoring and managing data warehouses
Lesson 3: Data Ingestion and Preparation
3.1 Introduction to data ingestion using Dataflow Gen2 and Data Pipeline
3.2 Creating and managing data pipelines for efficient data movement
3.3 Utilizing Dataflow Gen2 for data preparation and transformation
3.4 Best practices for data ingestion and preparation in Microsoft Fabric
Lesson 4: Lakehouses, Semi-Structured Data, and PySpark
4.1 Introduction to Lakehouse architecture in Microsoft Fabric
4.2 Storing and managing semi-structured data in Lakehouse
4.3 Working with Delta Lake tables for efficient data management
4.4 Utilizing PySpark for data transformation and analysis
Lesson 5: Medallion Architecture in Microsoft Fabric
5.1 Understanding the concept of Medallion Architecture
5.2 Designing and implementing a Medallion Architecture for data management
5.3 Organizing data lakes, data warehouses, and Lakehouse using Medallion Architecture principles
5.4 Best practices for creating scalable and efficient data architectures
Lesson 6: Exploring and Analyzing Data
6.1 Techniques for exploring and analyzing data in Microsoft Fabric
6.2 Utilizing Power BI for data exploration and visualization
6.3 Performing descriptive and diagnostic analysis on datasets
6.4 Extracting insights and making data-driven decisions
Lesson 7: Power BI and Data Visualization
7.1 Introduction to Power BI and its role in data visualization
7.2 Creating interactive Reports and Dashboards
7.3 Using Power BI for data exploration and analysis
7.4 Best practices for effective data visualization
Lesson 8: Designing and Building Semantic Models
8.1 Understand the importance of semantic modelling in data analytics
8.2 Designing tabular models for semantic analysis in Power BI
8.3 Implementing relationships and calculations using DAX
8.4 Optimizing semantic models for performance and scalability
8.5 Securities that can be implemented in Microsoft Fabric

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