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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. 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.

  4. Analytics - Wikipedia

    en.wikipedia.org/wiki/Analytics

    Data analysis focuses on the process of examining past data through business understanding, data understanding, data preparation, modeling and evaluation, and deployment. [8] It is a subset of data analytics, which takes multiple data analysis processes to focus on why an event happened and what may happen in the future based on the previous data.

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

    www.aol.com/depth-microsoft-excel-data-analysis...

    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. Microsoft Office - Wikipedia

    en.wikipedia.org/wiki/Microsoft_Office

    Microsoft Access is a database management system for Windows that combines the relational Access Database Engine (formerly Jet Database Engine) with a graphical user interface and software development tools. Microsoft Access stores data in its own format based on the Access Database Engine.

  7. 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 ]