



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.
Gesture Recognition is a technology that detects a user's physical movements (hand, arm, face, or body movements), transforming these gestures into digital commands.
Data matching is the process of linking a data field from one source to a data field from another source.
Cloud migration, one of the most important components of digital transformation, is the process of moving an organization's existing data, applications, and infrastructure to a cloud-based environment.
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