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  2. Microsoft Access - Wikipedia

    en.wikipedia.org/wiki/Microsoft_Access

    Microsoft Access is designed to scale to support more data and users by linking to multiple Access databases or using a back-end database like Microsoft SQL Server. With the latter design, the amount of data and users can scale to enterprise-level solutions. Microsoft Access's role in web development prior to version 2010 is limited.

  3. 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]

  4. Data science - Wikipedia

    en.wikipedia.org/wiki/Data_science

    Data science is "a concept to unify statistics, data analysis, informatics, and their related methods" to "understand and analyze actual phenomena" with data. [5] It uses techniques and theories drawn from many fields within the context of mathematics , statistics, computer science , information science , and domain knowledge . [ 6 ]

  5. This in-depth Microsoft Excel and data analysis training can ...

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    Now that you’ve successfully completed your first serious data analysis problem, learn the rest with the training available in The Premium 2021 Microsoft Excel and Data Certification Bundle.

  6. List of statistical software - Wikipedia

    en.wikipedia.org/wiki/List_of_statistical_software

    Ploticus – software for generating a variety of graphs from raw data; PSPP – A free software alternative to IBM SPSS Statistics; R – free implementation of the S (programming language) Programming with Big Data in R (pbdR) – a series of R packages enhanced by SPMD parallelism for big data analysis; R Commander – GUI interface for R

  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.

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