Business Intelligence (Class 8-9 Slide)

These flashcards cover key vocabulary and concepts in business intelligence and data management as discussed in the lecture.

Concept of Hierarchy

Represents a structured framework where concepts are categorized into superconcepts and subconcepts, such as employees, products, and customers.

OLAP

a category of software technology that enables analysts, managers, and executives to gain insight into data through fast, consistent, interactive access in various forms.

Data Warehouse

A central repository of integrated data from one or more disparate sources that stores current and historical data in one single place.

ROLAP

Relational OLAP; uses relational databases to store data and allows users to analyze data through a familiar SQL interface.

MOLAP

Multidimensional OLAP; stores data in multidimensional cubes, enabling fast access and complex analytics.

HOLAP

Hybrid OLAP; combines the capabilities of ROLAP and MOLAP for both large data volume queries and speedy analyses.

Data Mart

A subset of a data warehouse focused on a specific subject area or business line.

Data Mining

The process of discovering patterns and extracting valuable information from large sets of data.

Clustering

A data mining technique that groups similar objects into clusters based on characteristics and attributes.

Attribute Oriented Induction

A data generalization technique that summarizes and abstracts data based on the attributes present in the dataset.

Data Generalization

The process of abstracting detailed data to a higher conceptual level to understand broader patterns.

Data Cleaning

The process of identifying and correcting inaccuracies or incompleteness in data sets.

Data Reduction

The process of reducing the volume of data while maintaining its integrity and quality.

Hypothesis Driven Exploration

An exploratory type where discoveries are generated based on preconceived hypotheses.

Discovery Driven Exploration

An exploratory approach where exceptions and interesting patterns guide the data analysis process.

Segmentation by Natural Partitioning

The division of data into segments based on inherent distributions or patterns.

What is DATA MINING?

Data Miss Management and Data Removal 

End result of successful data mining process will have:

Data integration, data consolidation, data aggregation, decision management support

Instantiation

The process of creating an instance or occurrence of an object or class in programming or data analysis.

Example of Instantiation

lPerson = Person()