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Aggregate data is high-level data which is acquired by combining individual-level data. For instance, the output of an industry is an aggregate of the firms’ individual outputs within that industry. [1] Aggregate data are applied in statistics, data warehouses, and in economics. There is a distinction between aggregate data and individual data.
Disaggregated storage is a form of scale-out storage, built with some number of storage devices that function as a logical pool of storage that can be allocated to any server on the network over a very high performance network fabric. Disaggregated storage solves the limitations of storage area networks or direct-attached storage.
The information is packaged into aggregate reports and then sold to businesses, as well as to local, state, and government agencies. This information can also be useful for marketing purposes. In the United States, many data brokers' activities fall under the Fair Credit Reporting Act (FCRA) which regulates consumer reporting agencies .
An aggregate is a type of summary used in dimensional models of data warehouses to shorten the time it takes to provide answers to typical queries on large sets of data. The reason why aggregates can make such a dramatic increase in the performance of a data warehouse is the reduction of the number of rows to be accessed when responding to a query.
Composable disaggregated infrastructure (CDI), sometimes stylized as composable/disaggregated infrastructure, is a technology that allows enterprise data center operators to achieve the cost and availability benefits of cloud computing using on-premises networking equipment.
An aggregated distribution, commonly found among predators, parasites, and plants is a highly uneven statistical distribution pattern in which they collect or aggregate in regions. These regions may be widely separated, particularly within animal distributions that are influenced by prey or host densities.
For instance, if statistics for education and employment are aggregated separately, they cannot be used to explore a relationship between these two variables. Access to microdata allows researchers much more freedom to investigate such interactions and perform detailed analysis.
A post-Keynesian theory of aggregate demand emphasizes the role of debt, which it considers a fundamental component of aggregate demand; [7] the contribution of change in debt to aggregate demand is referred to by some as the credit impulse. [8] Aggregate demand is spending, be it on consumption, investment, or other categories. Spending is ...