in the 1980′s the notion of "Data Management" ascended as technology moved from sequential processing cards, then tape to random access processing. And now, it was technically possible to store a single data point in a single place and access that data using a random access disk. As applications became interactive it was obvious that both data management and processes management were equally important. If the data was not well defined, the application data would render poor results if on the other hand the process wasn't well defined, it became awkward to meet user needs.
Data analysis, also known as data analytics, is the process of examining, purging, converting, and modeling data with the aim of learning useful information, making inferences, and supporting decision-making. As a result of this evolution data analysis has developed multiple aspects and approaches, covering diverse modeling techniques under a variety of labels as it applies to different business, science, and social disciplines domains.
Data mining is a particular analytical technique that focuses on modeling and detection for predictive analysis rather than purely descriptive purposes. At the same time, business intelligence covers data analysis that depends on aggregation, focusing mainly on business information.
With the advent of powerful computing power another area of data analysis surged and it is being updated as it is being developed referred to as “Big Data” analysis that can operate with multiple algorithms designed to execute custom functionality for the user.
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