---
url: "https://xcademia.com/courses/microsoft-fabric-analytics-engineer-training"
title: Microsoft Fabric Analytics Engineer Training
description: "Learn Microsoft Fabric with this 4-day DP-600 training. Build analytics pipelines, models, and reports using OneLake and Power BI."
publishedAt: "2026-03-21T04:46:32.832096+00:00"
updatedAt: "2026-03-30T22:50:53.7265+00:00"
type: course
code: "CLD-0105"
level: Professional
duration_days: "4"
track: Azure Tracks
category: "Cloud & DevOps"
credential_tier: tier1
price_gbp: "1999"
---

# Microsoft Fabric Analytics Engineer Training

> Build analytics solutions using Microsoft Fabric aligned with DP-600 certification objectives. Learn data ingestion, transformation, modelling, and reporting using OneLake and Fabric tools.

## Overview

This Microsoft Fabric Analytics Engineer Training programme is designed for data professionals looking to build modern analytics solutions using Microsoft Fabric. Aligned with DP-600 certification objectives, the course provides a structured and hands-on approach to unified data analytics.

Through mentor-led sessions and practical labs, learners will ingest, transform, and model data using Fabric services such as OneLake, Dataflows, and Spark. The course also covers semantic models and reporting, enabling participants to create scalable and business-ready analytics solutions.

By the end of this programme, participants will be able to design end-to-end analytics solutions using Microsoft Fabric. This course prepares learners for analytics engineering roles and supports progression into data architecture, business intelligence, and advanced analytics pathways.

## Prerequisites

- Basic knowledge of data analytics and databases
- Familiarity with SQL and data modelling
- Understanding of cloud fundamentals

## What you will learn

- Design end-to-end analytics solutions
- Implement data ingestion and transformation pipelines
- Analyse and model data effectively
- Evaluate reporting and visualisation strategies
- Manage performance and optimisation
- Secure and govern analytics environments

## Skills you will gain

- Microsoft Fabric architecture
- Data ingestion and pipelines
- Data transformation and processing
- Semantic data modelling
- Power BI reporting
- Performance and cost optimisation

## Career progression

- Analytics Engineer
- Data Engineer
- BI Developer
- Data Analyst
- Data Platform Engineer

## Curriculum

1. **Module 1**
2. **Module 2**
3. **Module 3**
4. **Module 4**

## Exam & certification

This programme is aligned with the official exam objectives. Exam registration and certification are managed directly by the awarding body.

## Delivery options

- **Live Online** — Join live instructor-led sessions from anywhere. Interactive, engaging, and flexible.
- **Onsite Training** — We come to you. Training delivered at your workplace for teams of 6 or more.
- **Venue-Based** — Classroom training at a professional venue. Ideal for focused, immersive learning.
- **Blended** — Combine online and in-person learning for maximum flexibility and impact.

## Frequently asked questions

**Is this course aligned with DP-600 certification?**

Yes, it is aligned with Microsoft DP-600 certification objectives.



**Do I need prior Fabric experience?**

No, but basic knowledge of data analytics and SQL is recommended.



**Are hands-on labs included?**

Yes, extensive labs are included throughout the course.



**Does this course need an exam?**

No, the exam is optional and can be taken separately.



**What roles can I pursue after this course?**

Roles include Analytics Engineer, Data Engineer, and BI Developer.

## Course at a glance

| Field | Value |
| --- | --- |
| Code | CLD-0105 |
| Duration | 4 days |
| Level | Professional |
| Track | Azure Tracks |
| Category | Cloud & DevOps |
| Credential tier | tier1 |
| Price (GBP) | £1999 |

---

## About this content

This Markdown course profile is the citation-grade twin of [Microsoft Fabric Analytics Engineer Training](https://xcademia.com/courses/microsoft-fabric-analytics-engineer-training). It is published by **Xcademia** (UK Companies House 12322710) and is available for AI search engines and large language models to index, summarise, and cite.

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