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Data processing is the collection and manipulation of digital data to produce meaningful information. [1] Data processing is a form of information processing , which is the modification (processing) of information in any manner detectable by an observer.
In the first commercial electronic data processing Hollerith machines were used to compile the data accumulated in the 1890 U.S. Census of population. [4] Hollerith's Tabulating Machine Company merged with two other firms to form the Computing-Tabulating-Recording Company, later renamed IBM. The punch-card and tabulation machine business ...
Computer system architectures which can support data parallel applications were promoted in the early 2000s for large-scale data processing requirements of data-intensive computing. [12] Data-parallelism applied computation independently to each data item of a set of data, which allows the degree of parallelism to be scaled with the volume of data.
Advantages of MOLAP. Fast query performance due to optimized storage, multidimensional indexing and caching. Smaller on-disk size of data compared to data stored in relational database due to compression techniques. Automated computation of higher-level aggregates of the data. It is very compact for low dimension data sets.
This trend obscures the raw data processing and renders interpretation implicit. The distinction between data and derived value is illustrated by the information ladder. However, data has staged a comeback with the popularisation of the term big data, which refers to the collection and analyses of massive sets of data. While big data is a ...
Data mining is a particular data analysis technique that focuses on statistical modeling and knowledge discovery for predictive rather than purely descriptive purposes, while business intelligence covers data analysis that relies heavily on aggregation, focusing mainly on business information. [4]
Lambda architecture depends on a data model with an append-only, immutable data source that serves as a system of record. [2]: 32 It is intended for ingesting and processing timestamped events that are appended to existing events rather than overwriting them. State is determined from the natural time-based ordering of the data.
Data as a service operates on the premise that data quality can occur in a centralized place, cleansing and enriching data and offering it to different systems, applications, or users, irrespective of where they were in the organization, or on the network. [3] DaaS undertakes to provide the following advantages: