ETL VS Data Orchestration: Modern data management solutions
ETL is one of the well-known data management methodologies over the years and almost every company leverages one of ETL tool to effectively manage their data. Data orchestration is gaining popularity these days to compensate modern data requirements. We recently started working on modern technology stack like Azure Services (Azure data factory, Synapse), Apache Airflow, AWS Services (Glue, Lambda, Step functions) etc. and would like to share few insights on difference between traditional data management and modern data management.
ETL (Extract, Transform, Load):
Focuses on the specific process of data from one system to another, typically in batches.
Strengths:
Well-suited for structured, batch-based data processing. Easier to learn and use for simpler data pipelines.
ETL Tools:
Data Orchestration:
Acts like a conductor, managing and automating the execution of multiple data tasks and workflows.
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Choosing Between ETL and Data Orchestration:
In essence, ETL provides the core data transformation functionality, while data orchestration manages the broader workflow and execution. They can be complementary tools, with ETL processes being orchestrated within a larger data management framework.
we would like to discuss more on this area in upcoming sessions.
#DataEngineering #DataManagement #ETL #DataProcessing #DataIntegration #BigData #Analytics
Founder @ Bridge2IT +32 471 26 11 22 | Business Analyst @ Carrefour Finance
8 个月ETL - where raw data becomes valuable insights. Fascinating! ????