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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. 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.

4. Data science - Wikipedia

   en.wikipedia.org/wiki/Data_science

   Topological data analysis (TDA) is a mathematical framework that uses tools from topology, including algebraic, differential, and geometric topology, to study the shape and structure of data. In summary, data analysis and data science are distinct yet interconnected disciplines within the broader field of data management, analysis, and mathematics.

5. Data modeling - Wikipedia

   en.wikipedia.org/wiki/Data_modeling

   The data modeling process. The figure illustrates the way data models are developed and used today . A conceptual data model is developed based on the data requirements for the application that is being developed, perhaps in the context of an activity model.

6. Data mapping - Wikipedia

   en.wikipedia.org/wiki/Data_mapping

   Data transformation or data mediation between a data source and a destination; Identification of data relationships as part of data lineage analysis; Discovery of hidden sensitive data such as the last four digits of a social security number hidden in another user id as part of a data masking or de-identification project

7. Statistics - Wikipedia

   en.wikipedia.org/wiki/Statistics

   A typical "Business Statistics" course is intended for business majors, and covers [71] descriptive statistics (collection, description, analysis, and summary of data), probability (typically the binomial and normal distributions), test of hypotheses and confidence intervals, linear regression, and correlation; (follow-on) courses may include ...