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.
Data architecture is a set of rules, policies, standards, and models that govern and determine the type of data collected, and show how this data is used, stored, managed, and integrated within an enterprise and database systems.
Data security refers to the process of protecting corporate data and preventing data loss through unauthorized access.
SPSS (Statistical Package for the Social Sciences) is a popular software program used for statistical data analysis.
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