Data integration architectures
At first, the need for distinct data architectures didn’t seem crucial. However, over time, specialized and centralized architectures started to take shape. As needs diversified and grew, the demand for decentralized or microservice architectures also emerged, highlighting new requirements that had previously been overlooked.
Traditional data warehouses and ETL processes
Data warehouses have been at the core of data integration for decades. Traditional data warehouses are centralized repositories that are designed to store and manage large volumes of structured data from various sources. They enable organizations to consolidate their data, perform analytical queries, and generate valuable insights for informed decision-making.
One of the key aspects of traditional data warehouses is the ETL process. This process involves three main steps:
- Extract: Data is extracted from various sources, such as relational databases, flat files...
