![]() ![]() Predictive analysis uses historical data to make accurate forecasts about data patterns that may occur in the future. This may lead to the discovery that many customers visit a particular city to attend a monthly sporting event. Multiple data operations and transformations may be performed on a given data set to discover unique patterns in each of these techniques.For example, the flight service might drill down on a particularly high-performing month to better understand the booking spike. It is characterized by techniques such as drill-down, data discovery, data mining, and correlations. Diagnostic analysisĭiagnostic analysis is a deep-dive or detailed data examination to understand why something happened. Descriptive analysis will reveal booking spikes, booking slumps, and high-performing months for this service. It is characterized by data visualizations such as pie charts, bar charts, line graphs, tables, or generated narratives. For example, a flight booking service may record data like the number of tickets booked each day. Descriptive analysisĭescriptive analysis examines data to gain insights into what happened or what is happening in the data environment. It generally refers to the deviation from the mean.Data science is used to study data in four main ways: 1.
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