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  2. Data mining - Wikipedia

    en.wikipedia.org/wiki/Data_mining

    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 effectiveness of a marketing campaign, regardless of the amount of data. In contrast, data mining uses machine learning and statistical models to uncover clandestine or hidden patterns in a large ...

  3. Data Science and Predictive Analytics - Wikipedia

    en.wikipedia.org/wiki/Data_Science_and...

    The 14 chapters of the new edition start with an introduction and progressively build foundational skills to naturally reach biomedical applications of deep learning. Introduction; Basic Visualization and Exploratory Data Analytics; Linear Algebra, Matrix Computing, and Regression Modeling; Linear and Nonlinear Dimensionality Reduction

  4. Affinity analysis - Wikipedia

    en.wikipedia.org/wiki/Affinity_analysis

    This data mining method has been explored in different fields including disease diagnosis, market basket analysis, retail industry, higher education, and financial analysis. In retail, affinity analysis is used to perform market basket analysis, in which retailers seek to understand the purchase behavior of customers.

  5. Predictive analytics - Wikipedia

    en.wikipedia.org/wiki/Predictive_analytics

    Predictive analytics statistical techniques include data modeling, machine learning, AI, deep learning algorithms and data mining. Often the unknown event of interest is in the future, but predictive analytics can be applied to any type of unknown whether it be in the past, present or future.

  6. Data science - Wikipedia

    en.wikipedia.org/wiki/Data_science

    The modern conception of data science as an independent discipline is sometimes attributed to William S. Cleveland. [23] In 2014, the American Statistical Association's Section on Statistical Learning and Data Mining changed its name to the Section on Statistical Learning and Data Science, reflecting the ascendant popularity of data science. [24]

  7. Data analysis - Wikipedia

    en.wikipedia.org/wiki/Data_analysis

    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]

  8. Examples of data mining - Wikipedia

    en.wikipedia.org/wiki/Examples_of_data_mining

    Metabolomics is a very data heavy subject, and often involves sifting through massive amounts of irrelevant data before finding any conclusions. Data mining has allowed this relatively new field of medical research to grow considerably within the last decade, and will likely be the method of which new research is found within the subject. [28]

  9. Data warehouse - Wikipedia

    en.wikipedia.org/wiki/Data_warehouse

    Data Warehouse and Data mart overview, with Data Marts shown in the top right. In computing, a data warehouse (DW or DWH), also known as an enterprise data warehouse (EDW), is a system used for reporting and data analysis and is a core component of business intelligence. [1] Data warehouses are central repositories of data integrated from ...