Azure Data Engineer Free Demo from #sqlschool #azuredataengineer #freedemo

Introduction

Welcome to our comprehensive Azure Data Engineer course, designed to equip you with the knowledge and skills needed for success in data engineering. Here, we break down the essentials of data engineering, focusing on core activities, database types, and Modern Data Warehousing concepts, ensuring practical, step-by-step understanding. Our aim is to prepare you for the DP-203 certification—a vital credential for any aspiring data engineer.

Understanding Data Engineering

What is a Database?

A database serves as a platform for storing any type and amount of data. The main types include:

• OLTP (Online Transaction Processing) Database: Stores live, real-time data (e.g., a live car showroom).
• Data Warehouse: Stores historical and inactive data (e.g., temperature records over time).
• OAP Database: Focuses on analytical processing.

Our course primarily delves into Data Warehousing.

Responsibilities of a Data Engineer

As a data engineer, you're tasked with designing and managing data warehouses. You’ll work with existing OLTP databases to extract, join, and merge data. Furthermore, your duties may involve sourcing data from IoT devices, APIs, or various file types.

Workflow Overview

1. Data Extraction: Retrieve data from OLTP databases and other live sources.
2. Data Cleaning: Remove unnecessary data and refine it for transformation.
3. Transformation to Big Data Storage: Direct cleaned data to a warehouse for further processing.

ETL Technologies

We'll explore prominent ETL technologies, specifically:

• Data Factory: A versatile ETL tool.
• Databricks: Another powerful ETL option.
• Synapse: A data warehouse technology that complements ETL processes.

Data engineering involves seamless integration across these technologies to create an effective and scalable data architecture.

Course Structure

This course spans two months and covers:

• Storage solutions (data lakes and warehouses).
• ETL training via Data Factory and Synapse integration.
• Open-source tools like Spark for additional flexibility.

Every module incorporates practical examples and exercises to reinforce learning.

Conclusion

Our journey in combining Microsoft technologies—Azure Data Factory, Synapse, and Databricks—will prepare you well for certification and industry demands. We emphasize hands-on practices and real-world projects to help you build a robust resume.

Keyword

Keywords: Azure Data Engineer, SQL School, Free Demo, Data Warehouse, OLTP, Data Engineering, ETL Technologies, Databricks, Azure Data Factory, Synapse, Data Lake, Big Data, DP-203 Certification.

FAQ

1. What does the Azure Data Engineer course cover? The course focuses on data engineering principles, ETL technologies, database types, and the efficient use of Azure tools.

2. How long is the course? The course lasts two months, with options for regular or weekend classes.

3. What technologies will I learn? You will learn about Microsoft Azure tools like Data Factory, Synapse, and Databricks, alongside open-source technologies like Spark.

4. Is there a certification involved? Yes, the course prepares you for the DP-203 certification, validating your skills as a data engineer.

5. What is the structure of the classes? Classes are designed to be practical and engaging, with a mix of theoretical knowledge, real-life examples, and hands-on exercises.