Chapter 9 - Business Intelligence Flashcards
Data Acquisition
The process of obtaining, cleaning, organizing, relating, and cataloging source data.
Business Intelligence (BI) Systems
IS that process operational, social, and other data to identify patterns, relationships, and trends for use by business professionals and other knowledge workers.
BI Analysis
The process of creating business intelligence.
Push Publishing
Process of delivering BI to users without any request from the users; the results are delivered according to a schedule or as a result of an event it particular data condition.
Pull Publishing
Requires the user to request BI results.
Data Warehouse
A facility for managing an organization’s BI data.
Granularity
Refers to the level of detail represented by the data. Granularity can be either too fine or too coarse.
Data Mart
A data collection, smaller than a data warehouse, that addresses the needs of a particular department or functional area of the business.
Reporting Application
A BI application that inputs data from one or more sources and applies reporting operations to that data to produce BI reports.
RFM Analysis
Technique readily implemented with basic reporting operations, is used to analyze and rank customers according to their purchasing patterns. Considers how recently (R) and how frequently (F) a customer has ordered and how much money (M) the customer has spent.
OLAP
Online Analytical Processing. Dynamic. Viewer can change the report’s format. Has measures and dimensions. A measure is a data item of interest, that is to be summed, averaged or otherwise processed. A dimension is a characteristic of a measure. The report can also be called an OLAP cube.
Drill Down
To further divide the data into more detail.
Data Mining
The application if statistical techniques to find patterns and relationships among data for classification and prediction. Also referred to as Knowledge Discovery in Databases (KDD).
Unsupervised Data Mining
Analysts do not create a model or hypothesis before running the analysis. Analysts create a hypothesis after the analysis, in order to explain the patterns found.
Cluster Analysis
A common unsupervised technique that identifies groups of entities that have similar characteristics.
Supervised Data Mining
Data miners develop a model prior to the analysis and apply statistical techniques (such as regression) to data to estimate parameters of the model.
Neural Networks
A popular supervised data mining application used to predict values and make classifications such as “good prospect” or “poor prospect” customers.
Market-basket Analysis
An unsupervised data mining technique for determining sales patterns. Shows the products that customers tend to buy together. Creates a cross-selling opportunity.
Support (in Market-basket terminology)
The probability that two items will be purchased together.
Confidence (in Market-basket terminology)
A conditional probability estimate. The ratio of confidence to the base probability of buying an item is called lift.
Decision Tree
A hierarchical arrangement of criteria that predict a classification or a value. It is an unsupervised data mining technique. A common application of decision trees is to classify loans by likelihood of default.
MapReduce
A technique for harnessing the power of thousands of computers working in parallel. In the Map phase, BigData is broken down into pieces and sent to different computers. In the Reduce phase, the results are combined.
Hadoop
An open-source implementation of MapReduce supported by the Apache Foundation. Originally part of Cassandra. Includes a query language called Pig.
Knowledge Management (KM)
The process of creating value from intellectual capital and sharing that knowledge with employees, managers, suppliers, customers, and others who need that capital. KM improves process quality and increases team strength.
Expert Systems
Rule-based systems that encode human knowledge in the form of if/then rules.
Content Management Systems (CMS)
IS that supports the management and delivery of documents including reports, Web pages, and other expressions of employee knowledge.
Hyper-social Knowledge Management
The application of social media and related applications for the management and delivery of organizational knowledge resources.
Rich Directory
An employee directory that includes not only the standard name, email, phone, and address, but also organizational structure and expertise. The most popular rich directory is Microsoft’s Active Directory.
