Data gravity occurs when the volume of data in a warehouse increases and the number of uses also increases. In some cases, copying or moving data can be troublesome and expensive. Therefore, data tends to pull services, applications and other data into its warehouse. Primary examples of data gravity are data warehouses and data lakes. Data in these systems is inert. Scalable volumes of data often break existing infrastructure and processes, requiring risky and expensive fixes. Therefore, the best practice is to move design processing to data, not the other way around.
Reverse ETL is a data integration method in which traditional ETL (Extract, Transform, Load) processes reverse.
Micro-service architecture is a software architecture approach based on the development and deployment of large and complex applications as small, independent and specialized services.
GPT (Generative Pre-trained Transformer) is a model developed in the field of artificial intelligence, especially for natural language processing (NLP) applications.
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