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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.
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.
The storage limit using the 48-bit LBA ATA-6 standard introduced in 2002. 1.6 × 10 18 bits (200 petabytes) – total amount of printed material in the world [citation needed] 2 × 10 18 bits (250 petabytes) – storage space at Facebook data warehouse as of June 2013, [11] growing at a rate of 15 PB/month. [12] 2 61: 2,305,843,009,213,693,952 ...
Data analysis focuses on the process of examining past data through business understanding, data understanding, data preparation, modeling and evaluation, and deployment. [8] It is a subset of data analytics, which takes multiple data analysis processes to focus on why an event happened and what may happen in the future based on the previous data.
Data modeling is a process used to define and analyze data requirements needed to support the business processes within the scope of corresponding information systems in organizations.
Data mining is the process of extracting and discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, ...
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Data profiling utilizes methods of descriptive statistics such as minimum, maximum, mean, mode, percentile, standard deviation, frequency, variation, aggregates such as count and sum, and additional metadata information obtained during data profiling such as data type, length, discrete values, uniqueness, occurrence of null values, typical string patterns, and abstract type recognition.