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.
Regression is a technique that studies the relationship between a dependent variable (outcome) and one or more independent variables (inputs) in the processes of statistical modeling and data analysis.
A Business Continuity Plan (BCP) is a detailed document that shows how a business will continue to operate in the event of an unplanned interruption in service.
Data management is the implementation of policies and procedures that enable organizations to have control over business-critical data.
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