Processing B I Data
What are three techniques for processing B I data?
| B I Analysis Type | Goal | Characteristics |
| Reporting | Create information about past performance | Process structured data by sorting, grouping, summing, filtering, and formatting |
| Data mining | Classify and predict | Use sophisticated statistical techniques to find patterns and relationships |
| Big Data | Find patterns and relationships in Big Data | Volume, velocity, and variety force use of MapReduce techniques Some applications use reporting and data mining as well |
How recently (R) a customer has ordered
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.
