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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. 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 ]

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. Chief analytics officer - Wikipedia

   en.wikipedia.org/wiki/Chief_analytics_officer

   A similar position is that of the chief data officer (CDO); while the CDO focuses on data processing and maintenance, the CAO focuses on providing input into operational decisions on the basis of the analysis. As such, the CAO requires experience in statistical analysis and marketing, finance, or operations.

6. Business analytics - Wikipedia

   en.wikipedia.org/wiki/Business_analytics

   In other words, business intelligence focusses on description, while business analytics focusses on prediction and prescription. [1] Business analytics makes extensive use of analytical modeling and numerical analysis, including explanatory and predictive modeling, [2] and fact-based management to drive decision making.

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.

8. Scope statement - Wikipedia

   en.wikipedia.org/wiki/Scope_statement

   A scope statement should be written before the statement of work and it should capture, in very broad terms, the product of the project (e.g., "developing a software-based system to capture and track orders for software"). A scope statement should also include the list of users using the product, as well as the features in the resulting product ...

9. Data and information visualization - Wikipedia

   en.wikipedia.org/wiki/Data_and_information...

   Data visualization refers to the techniques used to communicate data or information by encoding it as visual objects (e.g., points, lines, or bars) contained in graphics. The goal is to communicate information clearly and efficiently to users. It is one of the steps in data analysis or data science. According to Vitaly Friedman (2008) the "main ...