The use of predictive analytics is a key milestone on your analytics journey — a point of confluence where classical statistical analysis meets the new world of artificial intelligence (AI). 

Prescriptive analytics focuses on finding the best course of action

in a scenario, given the available data. It’s related to both

descriptive analytics and

predictive analytics

Diagnostic analysis is referred to as root cause analysis. Diagostic analysis includes using processes such as data discovery, data mining, and drill down and drill through.

Descriptive analytics is a field of statistics that focuses on gathering and summarizing raw data to be easily interpreted.

Generally, descriptive analytics concentrate on historical data

Audio data analysis is about analyzing and understanding audio signals captured by digital devices, with numerous applications in the enterprise, healthcare, productivity, and smart cities.

Data exploration refers to the initial step in data analysis in which data analysts use data visualization and statistical techniques to describe dataset characterizations. such as size, quantity, and accuracy 

A distribution is simply a collection of data, or scores, on a variable. Usually, these scores are arranged in order from smallest to largest and then they can be presented graphically

Correlation is used to test relationships between quantitative variables or categorical variables. In other words, it’s a measure of how things are related.

Survival analysis corresponds to a set of statistical approaches used to investigate the time it takes for an event of interest to occur.