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Processing B I Data

 What are three techniques for processing B I data?

B I Analysis TypeGoalCharacteristics
ReportingCreate information about past performanceProcess structured data by sorting, grouping, summing, filtering, and formatting
Data miningClassify and predictUse sophisticated statistical techniques to find patterns and relationships
Big DataFind patterns and relationships in Big DataVolume, velocity, and variety force use of MapReduce techniques Some applications use reporting and data mining as well

How recently (R) a customer has ordered

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How frequently (F) a customer ordered

How much money (M) the customer has spent

RFM analysis is a technique readily implemented with basic reporting operations that is used to analyze and rank customers according to their purchasing patterns.

Online analytical processing (OLAP) is more generic than RFM and provides the ability to sum, count, average, and perform other simple arithmetic operations on groups of data.

An OLAP report has measures and dimensions.

A measure is the data item of interest. It is the item that is to be summed or averaged or otherwise processed in the OLAP report. Total sales, average sales, and average cost are examples of measures.

A dimension is a characteristic of a measure. Purchase date, customer type, customer location, and sales region are all examples of dimensions.

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