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2. 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 ...

3. List of statistical software - Wikipedia

   en.wikipedia.org/wiki/List_of_statistical_software

   Revolution Analytics – production-grade software for the enterprise big data analytics; RStudio – GUI interface and development environment for R; ROOT – an open-source C++ system for data storage, processing and analysis, developed by CERN and used to find the Higgs boson; Salstat – menu-driven statistics software

4. Computer-assisted qualitative data analysis software - Wikipedia

   en.wikipedia.org/wiki/Computer-assisted...

   Computer-assisted (or aided) qualitative data analysis software (CAQDAS) offers tools that assist with qualitative research such as transcription analysis, coding and text interpretation, recursive abstraction, content analysis, discourse analysis, [1] grounded theory methodology, etc.

5. List of Apache Software Foundation projects - Wikipedia

   en.wikipedia.org/wiki/List_of_Apache_Software...

   DataLab: platform for creating self-service, exploratory data science environments in the cloud using best-of-breed data science tools; DevLake: development data platform, providing the data infrastructure for developer teams to analyze and improve their engineering productivity; HugeGraph: a large-scale and easy-to-use graph database

6. 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.

7. Data science - Wikipedia

   en.wikipedia.org/wiki/Data_science

   Data analysis focuses on extracting insights and drawing conclusions from structured data, while data science involves a more comprehensive approach that combines statistical analysis, computational methods, and machine learning to extract insights, build predictive models, and drive data-driven decision-making. Both fields use data to ...