Hands-On Agile Coaching | Azure Data Engineer With Microsoft Fabric & Data Analytics

Course Overview

Unlock Your Potential with HAC's Azure Data Engineer Certification — Now Featuring Microsoft Fabric & Data Analytics.

Step into the future of data engineering with HAC’s comprehensive Azure Data Engineer Certification course, now updated to include Microsoft Fabric and cutting-edge Data Analytics practices. Designed by top industry experts, this course prepares you for the Microsoft Azure Data Engineering Exam: DP-203, equipping you with the skills to build scalable data storage solutions, design advanced data pipelines, and implement robust data security strategies.

Explore real-world industry use cases, tackle hands-on assignments, and experience immersive simulations that mirror today’s data challenges. With deep dives into Microsoft Fabric’s unified analytics capabilities and powerful integration tools, you’ll gain a competitive edge in the evolving data landscape.

Ignite your data career with HAC. Enroll today and embark on a transformative learning journey!

Course Objectives

Choose HAC's Microsoft Data Engineering Certification Course for mastering Azure data pipelines and stores. With expert instructors and practical learning, troubleshoot and optimize with ease. Elevate your career now!

Get a deep dive into essential subjects like Azure Cosmo DB, Azure Synapse, Azure Databricks, Azure Stream Analytics, Azure HDInsight, and Azure Data Factory.
Engage with assignments and quizzes within each module.
Participate in practice projects to refine your skills.
Access exam dumps featuring 100 scenario-based questions each, designed to aid your preparation for the certification exam.
Explore the comprehensive certification guide for DP-203.
Access interview preparation materials to aid in your interview readiness.
Unlock bonus and additional content to enhance your knowledge further.
Engage in capstone projects to strengthen your resume.
Acquire skills to architect scalable and resilient data solutions on the Azure platform.
Gain expertise in designing and optimizing data warehouses and data lakes using Azure services.
Develop proficiency in implementing data orchestration and automation solutions on Azure.

Hurry up and join our Microsoft Azure Data Engineer Certification Course today to propel your career to greater heights.

Enrolling in this course doesn't require predefined skills. However, familiarity with Linux, Python, SQL, and Scala would be advantageous.

Learning a DP-203 Certification Course can provide several benefits, such as:

Advancement in Career Opportunities:As the need for data engineering expertise grows, certified Azure Data Engineers are coveted by leading global firms. This creates numerous career prospects for professionals in this realm.
Anticipated Increase in Demand:The demand for proficient data engineers is expected to rise in the future, driven by the widespread adoption of cloud computing, big data analytics, and machine learning. This presents an opportune moment to pursue certification in Azure Data Engineering.
Skills:Obtaining the certification offers a thorough grasp of Azure data services, encompassing data modeling, ingestion, transformation, processing, analysis, visualization, monitoring, and optimization. This equips professionals to create and implement robust and efficient data pipelines and stores.
Increase in Salary Potential: Certified Azure Data Engineers often command higher salaries than their non-certified counterparts. This certification serves as a tangible demonstration of expertise and experience, paving the way for lucrative job prospects.
Practical Application Experience:Participants in the certification course gain practical experience through real-world case studies and industry projects, allowing them to apply their skills in authentic scenarios.

Our Azure Data Engineer Certification Course is crafted to industry standards, aiming to equip learners with the skills to design, implement, and uphold secure and compliant data processing pipelines utilizing Azure data services and frameworks. The course prepares candidates for the Azure Data Engineer Exam, assessing proficiency in integrating, transforming, and consolidating data from diverse sources.

Data modelling and database design
SQL and other query languages
Data integration and ETL Tools
Data analysis and visualization
Cloud Platform Skills
Programming languages such as Python and Java.
Data Pipeline Development

Key Topics Covered :

Azure for the Data Engineer:
- Cloud Computing basics
- Introduction to Microsoft Azure
- Applications of Azure
- Azure Services
- Understanding Data
- On-premises vs Cloud-based servers
- Azure Data Engineer roles & tasks
- Data Engineering processes
- cases for the Cloud
Data Engineering Services on Azure
- Azure Datalake Storage (ADLS) gen2
- Azure Blob Storage
- Azure SQL Database
- Azure Data Factory
- Azure Databricks
- Azure Synapse Analytics
- Microsoft Fabric
Data Storages on Azure:
- File stores
- Relational data store
- Non-Relational data stores
- Azure Blob storage
- NoSQL & Azure Cosmos DB
- Azure Data Lake Storage
- Why Data Lake
- Data Lake architecture
- Azure SQL Database
- Azure database for MySQL
- Azure database for MariaDB
- Azure database for PostgreSQL
- Azure Synapse Analytics

Azure Data Factory (ADF)

Introduction to Azure Data Factory (ADF)
ETL vs ELT
On-prem vs Cloud ETL tools
Why ADF
ADF Components
Linked Services in ADF
Integration Runtime (IR):
- Azure
- Self-hosted
- SSIS
Pipelines and activities:
- Copy data
- Control flow
- Data flow
Data Ingestion methods:
- Full load
- Copy data tool
- Batch load
- Sequential load
- Incremental load
- CDC

Working with various Copy data scenarios
Working with Azure SQL database
Working with Control flow activities
Working with Data Flow Transformations
Working with Parameters in ADF
SCD Type 1 & 2 Pipelines
ADF Data Migration
Scheduling & Triggering Pipelines
Monitoring Pipelines
CI/CD in ADF
ADF Projects

Python

Variables
Datatypes in Python
Operators in Python
Arithmetic
Logical
Comparison
Working with Strings
Indexing
Slicing
Data Structures in Python:
- List
- Tuples
- Sets
- Dictionaries

Functions:
- Built-in
- User defined
Conditional Flow Statements:
- If condition
- While loop
- For iteration
Range() function
Map
Filter
Reduce
Lambda expressions

Apache Spark

Introduction to Apache Spark
Hadoop vs Spark
Understanding Spark Architecture
Spark Context
Spark APIs
Spark Data structures:
- RDDs
- DataFrames
- Datasets
Creating Spark RDDs
Creating Spark DataFrames
Spark Actions
Lazy Evaluation
Fault Tolerance

Column manipulations:
- WithColumn
- WithColumnRenamed
Partitioning data using Partition by
Reading & Writing data of various formats
PySpark commands
Spark SQL
Group by & Aggregate Functions
Window Functions
Joins in PySpark
Date Functions
Conditional Functions
Caching
Schema evolution
DAG

Data Engineering with Azure Databricks

Introduction to Azure Databricks
Azure Databricks vs Databricks Community Edition
Databricks Runtime Engine
Databricks Components:
- Workspace
- Cluster
- Catalog
- DBFS
- Tables
- Hive Metastore
DBFS
Working with Files using DBUTILS
Creating Tables:
- using UI
- using Notebooks
Reading data from different files
Writing data to different formats
Visualization in Databricks Notebooks

Integrating Azure Blob with Databricks
Integrating ADLS with Databricks
Mounting with Access Keys
Secret Scopes using Azure Key Vault
Service Principle
SAS Tokens
Delta Lake
Creating Delta Tables:
- Managed tables
- External tables
Lakehouse
Medallion Architecture:
- Bronze layer
- Silver layer
- Gold layer
Scheduling Databricks Jobs using ADF Pipelines
Delta Live Tables (DLT)
Unity Catalog

Microsoft Fabric Data Engineering

Introduction to Microsoft Fabric
Fabric Analytics platform
Fabric OneLake
Fabric Data Factory:
- Data Pipelines
- Dataflows gen2
- Transforming data
- Loading data to Lakehouse
- Copy job
Create Pipeline in Fabric
Transform data with Dataflow gen2
ADF to Fabric migration
Fabric Synapse Data Engineering
Fabric Notebooks
Analyze data with Apache Spark
Lakehouse
Delta tables

Fabric Synapse Datawarehouse
Creating a Warehouse in Fabric
Ways to Load data into Warehouse
Creating Tables in Warehouse
Loading Data using COPY INTO Command
Loading Data using Pipeline to Warehouse
Loading Data using DataFlow Gen2
Lakehouse vs Warehouse
Microsoft Power BI in Fabric
Access data using PBI Desktop
Direct Lake
Direct Query
Row-level security
Column-level security

Hands-on Real-time ADE Scenarios
- Creating ETL/ELT Pipelines in Azure Data Factory
- Working with Control Flow activities in ADF Pipelines
- Working with Data Flow Transformations in ADF Pipelines
- Ingesting multiple File sources using ADF pipelines
- Ingesting multiple SQL tables using ADF Pipeline
- Implementing Batch load & Sequential load
- Incremental loading using last modify date & time
- Incremental loading and Change data capture
- SCD1 pipeline in ADF
- SCD2 pipeline in ADF
- Empty File scenarios
- Total File count in folder
- Validate Schema & Structure of files
- Copy data from Rest APIs
- Email Notifications
- Analyzing data with PySpark
- Analyzing data with Spark SQL
- Analyzing ADLS data from Databricks Notebooks
- Mounting & Service Principle
- Creating Delta Tables
- Lakehouse (Medallion) architecture
- Data Factory in Fabric
- Fabric Pipelines
- Fabric Dataflows gen2 to transform data
- Lakehouse in Fabric
- Warehouse in Fabric
- Visualizing data in Power BI
- Creating Dashboard in Power BI

DATA ANALYTICS

SQL
- SQL commands for Data Analysis (DDL & DML)
- Aggregate Functions & Grouping data
- SQL Joins & Set Operators
- Advanced Data Analysis: Subqueries
- Data Cleaning & Transformation
- Window & Logical Functions
- String & Date Functions
- Analytical Functions
Data Analytics with Power BI
- Introduction to Datawarehouse
- OLTP vs OLAP
- Star Schema vs Snowflake Schema
- Overview of Power BI
- Power BI Desktop
- Connecting Power BI with different data sources
- Power Query for Data Transformation
- Data Modeling
- DAX
- Reports & Visualization types
- Dashboards
- Publishing Reports
- Power BI Service

Real-time Projects

ADF Data Migration Project (migrating on-prem SQL Server data to Azure)
Incremental loading using Last Modified Date/Time
Incremental loading using CDC
SCD-2 Pipeline in ADF
End-to-End Databricks Project (Medallion Architecture)
Microsoft Fabric Project
Power BI Project

Bonuses

ADE Interview Questions and Answers
Mock Interviews
Placement Assistance
Fabric Certification (DP700) Support
Databricks certification support
Resume/CV Preparation
LinkedIn Profile Optimization

FAQ

A:The HAC's Microsoft Data Engineering training provides a deep grasp of Azure data engineering, enabling you to create, deploy, and oversee data solutions on Azure. Completing the DP-203 course earns you vital skills and certifications for career advancement.

A:Beginners can easily acquaint themselves with Azure data engineering services, as it is a user-friendly, cloud-based platform. To understand its capabilities and functionality, proper guidance and a well-structured training path are essential. Those interested in pursuing a career in data engineering using Azure can enroll in our online training program to earn certificates, showcasing their expertise in this domain.

A: Our instructors are experienced industry professionals having over 20 years of experience with extensive knowledge and expertise in software testing and quality assurance. They bring real-world experience and practical insights into the classroom, ensuring that you receive high-quality training from industry experts.

A: Yes, our course is available online, allowing you to learn at your own pace and convenience. You can access course materials, lectures, and assignments from anywhere, at any time, making it convenient for those with busy schedules.

A: We provide 24/7 expert support to our students. You can reach out to our instructors for guidance, clarification, or doubt clearing at any time during the course. We are committed to ensuring that you have the necessary support to succeed in your learning journey.

A: The duration of the course may vary, but typically it is designed to be completed in three weeks. However, as a benefit, once you have enrolled in the course, you can rejoin any other batch free of cost to reinforce your learning.

A: Yes, we provide a certification upon successful completion of the course. The certification validates your skills and knowledge in manual testing and quality assurance, which can be a valuable asset in your career advancement.

A: No, prior experience in software testing or IT is not necessary. Our course is designed for beginners as well as professionals who want to enhance their skills. Our instructors will provide the necessary guidance and support to help you understand the concepts and excel in the course.

A: We strive to provide high-quality training, but if you are not satisfied with the course, we offer a refund policy. Please refer to our refund policy for details.

A: Yes, you will have lifetime access to the course materials, lectures, and assignments even after the course completion. This allows you to revisit the content and reinforce your learning whenever needed.