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  2. Big data - Wikipedia

    en.wikipedia.org/wiki/Big_data

    Compared to survey-based data collection, big data has low cost per data point, applies analysis techniques via machine learning and data mining, and includes diverse and new data sources, e.g., registers, social media, apps, and other forms digital data. Since 2018, survey scientists have started to examine how big data and survey science can ...

  3. Big data maturity model - Wikipedia

    en.wikipedia.org/wiki/Big_Data_Maturity_Model

    The TDWI big data maturity model is a model in the current big data maturity area and therefore consists of a significant body of knowledge. [6] Maturity stages. The different stages of maturity in the TDWI BDMM can be summarized as follows: Stage 1: Nascent. The nascent stage as a pre–big data environment. During this stage:

  4. Data analysis - Wikipedia

    en.wikipedia.org/wiki/Data_analysis

    The data is necessary as inputs to the analysis, which is specified based upon the requirements of those directing the analytics (or customers, who will use the finished product of the analysis). [ 14 ] [ 15 ] The general type of entity upon which the data will be collected is referred to as an experimental unit (e.g., a person or population of ...

  5. Comparative research - Wikipedia

    en.wikipedia.org/wiki/Comparative_research

    Secondary analysis of quantitative data is relatively widespread in comparative research, undoubtedly in part because of the cost of obtaining primary data for such large things as a country's policy environment. This study is generally aggregate data analysis. Comparing large quantities of data (especially government sourced) is prevalent. [4]

  6. Critical data studies - Wikipedia

    en.wikipedia.org/wiki/Critical_data_studies

    First, 'big data' is an important aspect of twenty-first century society, and the analysis of 'big data' allows for a deeper understanding of what is happening and for what reasons. [1] Big data is important to critical data studies because it is the type of data used within this field.

  7. Topological data analysis - Wikipedia

    en.wikipedia.org/wiki/Topological_data_analysis

    Topological data analysis and persistent homology have had impacts on Morse theory. [149] Morse theory has played a very important role in the theory of TDA, including on computation. Some work in persistent homology has extended results about Morse functions to tame functions or, even to continuous functions [ citation needed ] .

  8. Eric Dickerson isn't rooting for Saquon Barkley to break his ...

    www.aol.com/sports/eric-dickerson-isnt-rooting...

    With 1,838 yards, the seven-year veteran has to average 133.5 yards in those final two games to seize the all-time mark. Barkley has topped that number in six of his 15 games this season.

  9. 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.