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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.
In many big data projects, there is no large data analysis happening, but the challenge is the extract, transform, load part of data pre-processing. [225] Big data is a buzzword and a "vague term", [226] [227] but at the same time an "obsession" [227] with entrepreneurs, consultants, scientists, and
Within some MOLAP systems the processing step (data load) can be quite lengthy, especially on large data volumes. This is usually remedied by doing only incremental processing, i.e., processing only the data which have changed (usually new data) instead of reprocessing the entire data set. Some MOLAP methodologies introduce data redundancy.
Neither the data collection, data preparation, nor result interpretation and reporting is part of the data mining step, although they do belong to the overall KDD process as additional steps. The difference between data analysis and data mining is that data analysis is used to test models and hypotheses on the dataset, e.g., analyzing the ...
Data collection or data gathering is the process of gathering and measuring information on targeted variables in an established system, which then enables one to answer relevant questions and evaluate outcomes. The data may also be collected from sensors in the environment, including traffic cameras, satellites, recording devices, etc.
Digital thread, also known as digital chain, [1] is defined as “the use of digital tools and representations for design, evaluation, and life cycle management.”. [2] It is a data-driven architecture that links data gathered during a Product lifecycle from all involved and distributed manufacturing systems. [3]
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.
The process of dimensional modeling builds on a 4-step design method that helps to ensure the usability of the dimensional model and the use of the data warehouse. The basics in the design build on the actual business process which the data warehouse should cover. Therefore, the first step in the model is to describe the business process which ...