Azure Data Engineer

Azure Data Engineers are responsible for integrating data from different data systems as well as setting up, managing and maintaining the data processing pipelines required for this. You will learn how artificial intelligence is used in the profession.
  • Certificates: Certificate "Azure Data Engineer"
  • Additional Certificates: Original Microsoft certificate "Microsoft Certified: Azure Administrator Associate"
    Certificate "Relational Databases SQL"
    Certificate "PCEP™ - Certified Entry-Level Python Programmer"
    Data Engineer" certificate
  • Examination: Practical project work with final presentations
    Microsoft certification exam AZ-104: Azure Administrator
    Certified Entry-Level Python Programmer (PCEP™) (in English)
  • Teaching Times: Full-time
    Monday to Friday from 8:30 a.m. to 3:35 p.m. (in weeks with public holidays from 8:30 a.m. to 5:10 p.m.)
  • Language of Instruction: German
  • Duration: 16 Weeks

Microsoft Azure Administration

Prerequisites for Azure administrators (approx. 1 day)

Azure portals (including PowerShell)

Resource Manager

Resources and resource groups

Azure templates (bicep files)


Managing Azure identities and governance (approx. 2 days)

Microsoft Entra ID

Users and groups

Device settings

Mass user updates

Guest accounts

Self-service password

Role-based access control (RBAC)

Access assignments

Directories

Subscriptions and governance: Azure policies, resources, tags

Cost management

Management groups


Configure and manage virtual networks (approx. 4.5 days)

Virtual networks

VNET peering

Private and public IP addresses, network routes, network interfaces, subnets and virtual networks

Name resolution: Azure DNS

Secure access to virtual networks

NSG to a subnet or network interface

Azure Bastion service

Load balancing with Application Gateway

Local connectivity

Network Performance Monitor

Network Watcher

Issues with external networks

Integrating a local network into an Azure virtual network

ExpressRoute

Azure WAN


Implement and manage storage space (approx. 2 days)

Storage accounts

Access signature

Access keys

Azure storage replication

Azure AD authentication

Azure Storage Explorer

AZCopy

Azure Files and Azure Blob Storage

Azure File Sharing

Azure File Synchronization Service


Artificial intelligence (AI) in the work process

Presentation of specific AI technologies

and possible applications in the professional environment


Provisioning and managing Azure computing resources (approx. 3.5 days)

Virtual Machines (VMs) for high availability and scalability

Azure Resource Manager template (ARM)

VHD template

Azure hard disk encryption

VM sizes

Adding data disks

Configuring the network

Containers

Container apps

Azure Container Instances (ACI)

Web apps


Monitoring and securing Azure resources (approx. 2 days)

Azure Monitor

metrics

Log Analytics

Diagnostic settings

Application Insights

Backup and restore operations

Backup reports

Azure backup service

Soft delete operation

Backup policies

Azure Site


Project work (approx. 5 days)

To consolidate the content learned

Presentation of the results

Certification exam AZ-104: Microsoft Azure Administrator

Relational databases with SQL

Basics of database systems and SQL (approx. 3 days)

Overview of database systems and models

Redundant data and data integrity

Normalization and BCNF

Database design and entity relationship model (ERM)

Primary and foreign keys

Relationships between relations

Data types in SQL

Indexes and performance

Constraints and validation

Queries (SQL)

Forms and reports in modern DBMS

Circular reference and dependency management


Introduction to SQL Server Management Studio (SSMS) (approx. 2 days)

Overview of SQL Server and SSMS

Physical database design

Creating tables and defining data types

Constraints, default values and relationships

Database diagrams and relationships

Backup and restore


Artificial intelligence (AI) in the work process

Presentation of specific AI technologies

and possible applications in the professional environment


Introduction to DDL (Data Definition Language) (approx. 8 days)

SQL basics and advanced syntax

Creating tables and defining constraints

Operators and function definitions

Queries and manipulation of data

Error handling and transaction management


DCL - Data Control Language and Security (approx. 1 day)

User administration and authorizations

Roles, authorizations and auditing


Data types, data import and export in modern systems (approx. 1 day)

Data import and export

Modern data types


Project work (approx. 5 days)

To consolidate the content learned

Presentation of the project results

Programming with Python

Python basics (approx. 1 day)

History, concepts

Usage and areas of application

syntax


First steps with Python (approx. 5 days)

Numbers

Strings

Date and time

Standard input and output

list, tuple dict, set

Branches and loops (if, for, while)


Artificial intelligence (AI) in the work process

Presentation of specific AI technologies

and possible applications in the professional environment


Functions (approx. 5 days)

Define your own functions

Variables

Parameters, recursion

Functional programming


Troubleshooting (approx. 0.5 days)

try, except

Intercept program interruptions


Object-oriented programming (approx. 4.5 days)

Python classes

Methods

Immutable objects

Data class

Inheritance


Graphical user interface (approx. 1 day)

Buttons and text fields

Grid layout

File selection


Project work, certification preparation and certification exam "PCEP™ - Certified Entry-Level Python Programmer" in English (approx. 3 days)

Data Engineer

Basics of Business Intelligence (approx. 2 days)

Fields of application, dimensions of a BI architecture

Basics of business intelligence, OLAP, OLTP, tasks of data engineers

Data Warehousing (DWH): handling and processing of structured, semi-structured and unstructured data


Requirements management (approx. 2 days)

Tasks, objectives and procedures in requirements analysis

Data modeling, introduction/modeling with ERM

Introduction/modeling in UML

- Class diagrams

- Use case analysis

- Activity diagrams


Artificial intelligence (AI) in the work process

Presentation of specific AI technologies

and possible applications in the professional environment


Databases (approx. 3 days)

Basics of database systems

Architecture of database management systems

Application of RDBMS

Implementation of data model in RDBMS, normal forms

Practical and theoretical introduction to SQL

Limits of relational databases, csv, json


Data Warehouse (approx. 4 days)

Star Schema

Data modeling

Creation of Star Schema in RDBMS

Snowflake Schema, basics, data modeling

Creation of Snowflake Schema in RDBMS

Galaxy Schema: Basics, data modeling

Slowly Changing Dimension Tables Type 1 to 5 - Restating, Stacking, Reorganizing, mini Dimension and Type 5

Introduction to normal, causal, mini and monster, heterogeneous and sub dimensions

Comparison of state and transaction oriented

Fact tables, density and storage from DWH


ETL (approx. 4 days)

Data Cleansing

- Null Values

- Preparation of data

- Harmonization of data

- Application of regular expressions

Data Understanding

- Data validation

- Statistical data analysis

Data protection, data security

Practical structure of ETL routes

Data Vault 2.0, basics, hubs, links, satellites, hash key, hash diff.

Data Vault data modeling

Practical structure of a Data Vault model - Raw Vault, practical implementation of hash procedures


Project work (approx. 5 days)

To consolidate the content learned

Presentation of the project results



Changes are possible. The course content is updated regularly.

Basic knowledge of Azure administration is required. Knowledge of English for the Python certification exam is required.

After this course, you will have in-depth knowledge of Azure configuration and administration. Python and SQL skills complete your profile and you can combine these with the tasks of Data Engineers.

IT and network specialists, (specialist) computer scientists, people with practical experience and good knowledge of IT.

As companies need to manage and structure ever-increasing amounts of data to evaluate and target their business processes, skills in data development and construction are in demand in all industries.

Your meaningful certificate provides a detailed insight into the qualifications you have acquired and improves your career prospects.

Didactic concept

Your lecturers are highly qualified both professionally and didactically and will teach you from the first to the last day (no self-study system).

You will learn in effective small groups. The courses usually consist of 6 to 25 participants. The general lessons are supplemented by numerous practical exercises in all course modules. The practice phase is an important part of the course, as it is during this time that you process what you have just learned and gain confidence and routine in its application. The final section of the course involves a project, a case study or a final exam.

 

Virtual classroom alfaview®

Lessons take place using modern alfaview® video technology - either from the comfort of your own home or at our premises at Bildungszentrum. The entire course can see each other face-to-face via alfaview®, communicate with each other in lip-sync voice quality and work on joint projects. Of course, you can also see and talk to your connected trainers live at any time and you will be taught by your lecturers in real time for the entire duration of the course. The lessons are not e-learning, but real live face-to-face lessons via video technology.

 

The courses at alfatraining are funded by Agentur für Arbeit and are certified in accordance with the AZAV approval regulation. When submitting a Bildungsgutscheinor Aktivierungs- und Vermittlungsgutschein, the entire course costs are usually covered by your funding body.
Funding is also possible via Europäischen Sozialfonds (ESF), Deutsche Rentenversicherung (DRV) or regional funding programs. As a regular soldier, you have the option of attending further training courses via Berufsförderungsdienst (BFD). Companies can also have their employees qualified via funding from Agentur für Arbeit (Qualifizierungschancengesetz).

We will gladly advise you free of charge. 0800 3456-500 Mon. - Fri. from 8 am to 5 pm
free of charge from all German networks.
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We will gladly advise you free of charge. 0800 3456-500 Mon. - Fri. from 8 am to 5 pm free of charge from all German networks.