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The DP-600: Microsoft Fabric Analytics Engineer course is designed to provide learners with comprehensive knowledge and hands-on experience in end-to-end analytics using Microsoft Fabric. The course covers a wide range of topics, from introduction to analytics to Administering Microsoft Fabric, Data ingestion, and data management. Learners will gain practical skills in using Dataflows Gen2, Spark, Data Factory pipelines, and managing Lakehouses within Microsoft Fabric.
Throughout the modules, participants will learn about organizing data using the Medallion architecture design, working with Apache Spark, Delta Lake tables, and securing their data environments. The course also delves into Data warehousing, teaching how to load, query, monitor, optimize, and model data warehouses. Moreover, it addresses scalability in Power BI, creating model relationships, performance optimization tools, and enforcing model security. This extensive training is crucial for those looking to excel in managing and analyzing data with Microsoft's analytics tools.
Successfully delivered 162 sessions for over 7,677 professionals
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| Course Fee | 1,475 |
|
Total Fees (without exam) |
1,475 (USD) |
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Free Pre-requisite TrainingJoin a free session to assess your readiness for the course. This session will help you understand the course structure and evaluate your current knowledge level to start with confidence.
Assessments (Qubits)Take assessments to measure your progress clearly. Koenig's Qubits assessments identify your strengths and areas for improvement, helping you focus effectively on your learning goals.
Post Training ReportsReceive comprehensive post-training reports summarizing your performance. These reports offer clear feedback and recommendations to help you confidently take the next steps in your learning journey.
Class RecordingsGet access to class recordings anytime. These recordings let you revisit key concepts and ensure you never miss important details, supporting your learning even after class ends.
Free Lab ExtensionsExtend your lab time at no extra cost. With free lab extensions, you get additional practice to sharpen your skills, ensuring thorough understanding and mastery of practical tasks.
Free Revision Classes Join our free revision classes to reinforce your learning. These classes revisit important topics, clarify doubts, and help solidify your understanding for better training outcomes.
Inclusions in Koenig's Learning Stack may vary as per policies of OEMs
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♱ Excluding VAT/GST
You can request classroom training in any city on any date by Requesting More Information
Inclusions in Koenig's Learning Stack may vary as per policies of OEMs
Prem Nidhi Sharma
SSIS|SSRS|Azure Databricks|SQL Server|Database Administration|Azure Data Factory|Data Modelling and Design
I am a Database Administrator (on-prem and Azure) and Microsoft Certified Trainer with around 15 years of rich experience in imparting training on Microsoft Database Administration along with Database Development (trained global clients such as HCL, Wipro, Cognizant, and Infosys)
You should be familiar with basic data concepts and terminologies related to data engineering, data modeling, and data analytics. Working knowledge of PySpark is recommended.
| Exam Component | Details |
|---|---|
| Exam Name | DP-600T00: Microsoft Fabric Analytics Engineer |
| Exam Type | Multiple Choice Questions (MCQs) |
| Total Questions | [Expected Number of Questions] |
| Passing Score | [Required Passing Score] |
| Exam Duration | [Duration in Minutes] |
| Language | English |
| Exam Provider | Microsoft |
| Exam Registration | Through Microsoft's official certification website or authorized testing centers |
| Certification Validity | [Validity Period, e.g., 1 year or 2 years, with renewal options] |
| Recommended Training | [Related Training Course Offered by Microsoft] |
The DP-600 course offers comprehensive training in Microsoft Fabric analytics, catering to IT professionals in data roles.
This DP-600 course equips learners with end-to-end analytics skills on Microsoft Fabric, focusing on data ingestion, management, security, and optimization within the Microsoft ecosystem.
Learning objectives and outcomes:
