Term
|
Definition
| Patterns, relationships and trends identified by BI systems. |
|
|
Term
| Business Intelligence (BI) Systems |
|
Definition
| Information systems that process operational and other data to analyze other data and make predictions. |
|
|
Term
|
Definition
| The software component of a BI system |
|
|
Term
|
Definition
| Decision making part of BI systems |
|
|
Term
|
Definition
| The process of obtaining, cleaning, organizing, relating cataloging source data. |
|
|
Term
|
Definition
| The process of creating business intelligence. Consists of 3 fundamental parts: Reporting, data mining, and Big Data. |
|
|
Term
| What are the 3 primary activities in the BI process? |
|
Definition
| Acquire data, perform analysis, and publish results. |
|
|
Term
|
Definition
| Process of delivering business intelligence to the knowledge workers who need it. |
|
|
Term
|
Definition
| delivers business intelligence to users without any request from the users, but according to a schedule or as a result of an event or particular data condition. |
|
|
Term
|
Definition
| requires the user to request BI results |
|
|
Term
|
Definition
| facility for managing an organizations BI data. It takes data from operational systems and purchased data, cleans and processes the data, and locates the data on the "shelves" of the data warehouse. |
|
|
Term
|
Definition
| Data collection, smaller than data warehouse, that addresses the needs of a particular department or functional area of the business. |
|
|
Term
|
Definition
| The process of sorting, grouping, summing, filtering and formatting structured data. |
|
|
Term
|
Definition
| In the form of rows and columns, tables in a relational database or a spreadsheet data. |
|
|
Term
|
Definition
| reports produced when something out of predefined bounds occurs |
|
|
Term
|
Definition
| Application of statistical techniques to find patterns and relationships among data for classification and predictions. 2 categories, supervised and unsupervised. |
|
|
Term
|
Definition
| analysts do not create a model or hypothesis before running the analysis. |
|
|
Term
|
Definition
| Statistical techniques that identify groups of entities that have similar characterisitics |
|
|
Term
|
Definition
| data miners develop a model prior to the analysis and apply statistical techniques to data to estimate parameters of the model |
|
|
Term
|
Definition
| measures the impact of a set of variables on another variable |
|
|
Term
|
Definition
| a term to describe data collections that are characterized by huge volume (petabyte in size or larger), rapid velocity,(generated rapidly) and great variety (different formats). |
|
|
Term
|
Definition
| technique for harnessing the power of thousands of computers working in parallel |
|
|
Term
|
Definition
| an open source program associated with the Apache foundation that manages thousands of computers and which implements MapReduce. |
|
|
Term
|
Definition
| Query language that Hadoop uses |
|
|
Term
|
Definition
| BI dicuments that are fixed at the time of creation and do not change, mostly published as PDF documents. |
|
|
Term
|
Definition
| BI documents that are updated at the time they are requested |
|
|
Term
|
Definition
| User requests for particular BI results on a particular schedule or in response to particular events. |
|
|
Term
|
Definition
| Web server application that is purpose-built for the publishing of business intelligence |
|
|
Term
|
Definition
| Application of business intelligence systems to the planning and execution of marketing programs. |
|
|
Term
|
Definition
| A way of analyzing and ranking customers according to their purchase patterns. |
|
|
Term
|
Definition
| Customers with the most recent orders are given a score of 1 to 5. |
|
|
Term
|
Definition
| Customers who order the most frequently are given a score of 1 to 5. |
|
|
Term
|
Definition
| Customers who have ordered the most expensive items are given a score 1 to 5. |
|
|
Term
|
Definition
| A data mining technique for determining sales pattern, products that a customer tends to buy together. |
|
|
Term
|
Definition
| An opportunity to sell more products to customers by using market-basket analysis |
|
|
Term
|
Definition
| the probability that 2 items will be purchased together, found by examining sales transactions and counting the number of times that that 2 items occur in the same transaction |
|
|
Term
|
Definition
| conditional probability estimate in market-basket terminology |
|
|
Term
|
Definition
| the ratio of confidence to the base probability of buying an item |
|
|
Term
|
Definition
| A hierrachical arrangement of of criteria that predict a classification or a value, an unsupervised data mining technique |
|
|