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.
Meta Data is data that describes other data in a structured, consistent form, so that large amounts of data can be collected, stored, and analyzed over time.
Financial analytics, also known as financial analytics, provides different perspectives on financial data related to a particular business, providing insights that will facilitate strategic decisions and actions that will improve the overall performance of the business.
Generative Adversarial Networks (GANs) are an innovative AI architecture in which two AI models work in competition. GANs are particularly used for the production of realistic images, videos and other digital content and have revolutionized creative AI projects.
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