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  2. 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]

  3. Data Analytics Library - Wikipedia

    en.wikipedia.org/wiki/Data_Analytics_Library

    Principal Component Analysis (PCA): the most popular algorithm for dimensionality reduction. Association rules mining: Detecting co-occurrence patterns. Commonly known as “shopping basket mining.” Data transformation through matrix decomposition: DAAL provides Cholesky, QR, and SVD decomposition algorithms.

  4. Geographic information system - Wikipedia

    en.wikipedia.org/wiki/Geographic_Information_System

    GIS data acquisition includes several methods for gathering spatial data into a GIS database, which can be grouped into three categories: primary data capture, the direct measurement phenomena in the field (e.g., remote sensing, the global positioning system); secondary data capture, the extraction of information from existing sources that are ...

  5. WorldQuant University - Wikipedia

    en.wikipedia.org/wiki/WorldQuant_University

    The Applied Data Science Lab is a free, credentialed offering where students use data analysis to solve real-world meaningful, and complex problems. During this self-paced course, students complete eight projects that range from exploring housing prices in Mexico to predicting air quality in Kenya.

  6. Data science - Wikipedia

    en.wikipedia.org/wiki/Data_science

    Data analysis typically involves working with smaller, structured datasets to answer specific questions or solve specific problems. This can involve tasks such as data cleaning, data visualization, and exploratory data analysis to gain insights into the data and develop hypotheses about relationships between variables. Data analysts typically ...

  7. Exploratory data analysis - Wikipedia

    en.wikipedia.org/wiki/Exploratory_data_analysis

    Exploratory data analysis is an analysis technique to analyze and investigate the data set and summarize the main characteristics of the dataset. Main advantage of EDA is providing the data visualization of data after conducting the analysis.

  8. Analyst's Notebook - Wikipedia

    en.wikipedia.org/wiki/Analyst's_Notebook

    i2 Analyst's Notebook is a software product from i2 Group for data analysis. Based on ELP (entity-link-property) methodology, it reveals relationships between data entities to discover patterns and provide insight into data. It is commonly used by digital analysts at law enforcement, military and other government intelligence agencies, and by ...

  9. Origin (data analysis software) - Wikipedia

    en.wikipedia.org/wiki/Origin_(data_analysis...

    Older (.OPJ), but not newer (.OPJU), Origin project files can be read by the open-source LabPlot or SciDAVis software. The files can also be read by QtiPlot but only with a paid "Pro" version. Finally the liborigin [1] library can also read .OPJ files such as by using the opj2dat script, which exports the data tables contained in the file.