Modern Data Architectures Training
Level
IntermediateDuration
24h / 3 daysDate
Individually arrangedPrice
Individually arrangedModern Data Architectures Training
This training is designed for professionals working with data who want to learn and implement modern data architecture models. Over 3 intensive days, participants will learn how to choose the right architecture for specific business and technological requirements, understand practical differences between approaches (Data Vault, Lakehouse, Medallion, etc.), and implement and manage ETL/ELT processes using tools such as Spark and Docker.
What You Will Learn
- Choose the right data architecture for organizational goals and scale
- Differentiate approaches: Data Vault, Lakehouse, Medallion, Kimball, Inmon
- Understand types of architectures, their pros/cons, and implementation methods
- Learn data processing methods (ETL/ELT processes)
Requirements
- Ability to run a Python environment (3.10 or higher)
- Ability to work with Docker
Who is this training for?
Data Engineers, Data Analysts, Data Designers who want to deepen their knowledge of modern data architectures and models-
Solution Architects designing data environment solutions
-
Professionals involved in implementation projects, warehouse modernization, and building Data Lakes/Lakehouses
Training Program
-
Day 1: Data Foundations and Architectures
- Introduction
- Data basics: data types, normalization, standardization
- Data structures
- Inmon architecture
- Kimball architecture
- Data Vault architecture
-
Day 2: Modern Data Platforms and Architectures
- Table format overview
- Introduction to Apache Spark
- Data Lake architecture
- Data Lakehouse architecture
- Medallion architecture
- Unity Catalog
-
Day 3: Data Engineering, Governance, and Quality
- Implementing ETL and ELT processes
- Data Governance
- Data Compliance
- Data Quality and Data Profiling
