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2. Data processing - Wikipedia

   en.wikipedia.org/wiki/Data_processing

   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.

3. Data science - Wikipedia

   en.wikipedia.org/wiki/Data_science

   Data science is an interdisciplinary academic field [1] that uses statistics, scientific computing, scientific methods, processing, scientific visualization, algorithms and systems to extract or extrapolate knowledge and insights from potentially noisy, structured, or unstructured data. [2]

4. KNIME - Wikipedia

   en.wikipedia.org/wiki/KNIME

   KNIME (/ n aɪ m / ⓘ), the Konstanz Information Miner, [2] is a free and open-source data analytics, reporting and integration platform.KNIME integrates various components for machine learning and data mining through its modular data pipelining "Building Blocks of Analytics" concept.

5. Data analysis - Wikipedia

   en.wikipedia.org/wiki/Data_analysis

   Data analysis is a process for obtaining raw data, and subsequently converting it into information useful for decision-making by users. [1] Data is collected and analyzed to answer questions, test hypotheses, or disprove theories. [11] Statistician John Tukey, defined data analysis in 1961, as:

6. Data engineering - Wikipedia

   en.wikipedia.org/wiki/Data_engineering

   Around the 1970s/1980s the term information engineering methodology (IEM) was created to describe database design and the use of software for data analysis and processing. [3] [4] These techniques were intended to be used by database administrators (DBAs) and by systems analysts based upon an understanding of the operational processing needs of organizations for the 1980s.

7. Online machine learning - Wikipedia

   en.wikipedia.org/wiki/Online_machine_learning

   In computer science, online machine learning is a method of machine learning in which data becomes available in a sequential order and is used to update the best predictor for future data at each step, as opposed to batch learning techniques which generate the best predictor by learning on the entire training data set at once. Online learning ...

8. Training, validation, and test data sets - Wikipedia

   en.wikipedia.org/wiki/Training,_validation,_and...

   A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]

9. Electronic data processing - Wikipedia

   en.wikipedia.org/wiki/Electronic_data_processing

   Invalid or incorrect data needed correction and resubmission with consequences for data and account reconciliation. Data storage was strictly serial on paper tape, and then later to magnetic tape: the use of data storage within readily accessible memory was not cost-effective until hard disk drives were first invented and began shipping in 1957.