Object Oriented Database Object
Class Inheritance
Encapsulation Polymorphism
Association Aggregation

 

A fundamental unit in an object-oriented database, representing a specific instance of a class with its own properties and behaviors. A database that supports the modeling and creation of objects, including their properties, relationships, and methods.
A mechanism in object-oriented databases that allows classes to inherit properties and behaviors from other classes, forming a hierarchy. A blueprint or template for creating objects in an object-oriented database, defining their common properties and behaviors.
The ability of objects in an object-oriented database to take on multiple forms and exhibit different behaviors based on the context. The bundling of data and methods within a class in an object-oriented database, hiding the internal implementation details.
A special type of association in an object-oriented database where one object represents a collection of other related objects. A relationship between objects in an object-oriented database, typically represented by a reference or link between them.

 

Query Language Database Segmentation
Segment Segmentation Criteria
Segmentation Strategy Data Type
Geographic Segmentation Demographic Segmentation

 

The process of dividing a large database into smaller, more manageable segments based on criteria such as data type, geography, or customer demographics. A language used to interact with an object-oriented database, allowing users to retrieve and manipulate data stored in objects.
The specific criteria or factors used to divide a database into segments, such as age, income level, or product preferences. A distinct portion or subset of a database resulting from the process of database segmentation.
The classification or categorization of data into different types such as numeric, text, date, or Boolean. The overall approach or plan for dividing a database into segments in order to better target marketing efforts or improve data management.
Dividing a database into segments based on demographic factors such as age, gender, income, or occupation. Dividing a database into segments based on geographic factors such as country, region, or postal code.

 

Psychographic Segmentation Behavioral Segmentation
Customer Segmentation Data Warehousing
ETL Fact Table
Data Mart OLAP

 

Dividing a database into segments based on behavioral factors such as purchase history, website activity, or response to marketing campaigns. Dividing a database into segments based on psychological factors such as lifestyles, attitudes, or values.
The process of collecting, organizing, and storing data to be retrieved and analyzed later. The process of dividing a database into segments based on customer-related factors in order to target marketing efforts and personalize communication.
A central table in a data warehouse that contains the primary measures or metrics of a business process. The process of extracting data from various sources, transforming it to fit the data warehouse schema, and loading it into the data warehouse.
The capability of a system to provide multidimensional analysis of data in a data warehouse. A smaller, specialized subset of a data warehouse that is focused on a particular business function or department.

 

Data Mining Data Cleansing
Business Intelligence Data Analysis
Dashboard Predictive Analytics
Data Visualization Extract

 

The process of identifying and correcting or removing errors, inconsistencies, and inaccuracies in data stored in the data warehouse. The process of discovering patterns, insights, and valuable information from large datasets stored in the data warehouse.
The process of inspecting, cleaning, transforming, and modeling data to discover useful information that can support decision-making in business intelligence. A technology-driven process for analyzing data and presenting actionable information to help corporate executives, business managers, and other end-users make more informed business decisions.
Using statistical techniques and machine learning algorithms to analyze current and historical data to make predictions about future events and outcomes in business intelligence. A visual display of key performance indicators (KPIs) and other important business metrics, providing a real-time snapshot of the organization's performance.
The first step in the Extract, Transform, Load (ETL) process, which involves retrieving data from various sources, such as databases, files, or APIs. The graphical representation of information and data, using visual elements such as charts, graphs, and maps, to facilitate understanding and decision-making in business intelligence.

 

Transform Load
Extraction Validation
ETL Tool Real Time Updates
Change Data Capture Batch Processing

 

The third and final step in the ETL process, which involves transferring the transformed data into the target database, data warehouse, or application. The second step in the ETL process, which involves converting and restructuring the extracted data into a format suitable for the destination system or application.
The process of ensuring the accuracy, completeness, and quality of the extracted and transformed data. The process of retrieving or pulling data from the source systems or applications.
The process of updating data in a data warehouse as soon as new information becomes available. A software tool or platform that facilitates the automation and management of the Extract, Transform, Load process.
Processing data in large blocks at scheduled intervals. The process of identifying and capturing changes made to data in real time, enabling real time updates to data warehouses.

 

Data Latency Event Driven Architecture
Micro-Batch Processing Real-Time Analytics
Multi-Dimensional Databases Dimensions
Cubes Measures

 

A design pattern where the flow of the application is determined by events that occur, rather than being controlled by a central program flow. The delay between data being generated and being available for reporting and analysis in a data warehouse.
The analysis of data as soon as it is acquired, often used to make immediate decisions or respond to events as they happen. Where data is processed in small, fixed-size batches rather than processing the data all at once.
The different attributes or aspects of data that can be used for analysis and organization in a multi-dimensional database. A type of database that is designed to store and query data with multiple dimensions, such as time, location, and product.
The numerical values or metrics that are stored in a multi-dimensional database and can be analyzed and aggregated. The main structures in a multi-dimensional database that contain the actual data and are used for analysis and reporting.

 

Hierarchies Slicing
Dicing Roll-Up
Drill-Down Network Data Model
Graph Node

 

The process of selecting a subset of data from a multi-dimensional database based on specific criteria or filters. The levels of organization or categorization within dimensions in a multi-dimensional database, such as year, quarter, and month in a time dimension.
The process of aggregating data from lower-level hierarchies to higher-level hierarchies in a multi-dimensional database. The process of selecting multiple subsets of data from a multi-dimensional database based on multiple criteria or filters.
A type of data model that represents data as nodes and edges, where nodes are entities and edges are relationships between them. The process of navigating from a higher-level hierarchy to a lower-level hierarchy in a multi-dimensional database to view more detailed data.
An individual entity or record within a network data model or graph structure A collection of nodes and edges that are used to represent a network data model.

 

Edge Attribute
Directed Graph Undirected Graph
Spatial Database Geometric Data Types
Spatial Queries Urban Planning

 

A property or characteristic of a node in a network data model. A connection or relationship between two nodes in a network data model or graph structure.
A graph in which edges do not have a specific direction, indicating non-specific relationships between nodes. A graph in which edges have a specific direction, indicating relationships between nodes.
Data types that represent geometric objects such as points, lines, and polygons, allowing for the modeling of spatial features in a database. A type of database specifically designed to store and manage spatial data, which includes information about the position, shape, and relationship of objects in space.
A discipline that focuses on the development and design of land use and the built environment. Queries that involve location-based conditions, enabling the retrieval of data based on spatial relationships and geographic criteria.

 

Environmental Monitoring Transportation Systems
Point Line
Polygon Raster Data Model
Cell Scalability

 

A network designed for the movement of people and goods, encompassing various modes of transport. The process of systematically sampling the environment to analyze and track changes over time.
A depiction of connections or paths between points, represented as a sequence of coordinates, used for mapping linear features. A specific location in a given space represented by a set of coordinates, such as latitude and longitude.
A method of representing spatial data through a grid of cells, where each cell holds a specific value representing a characteristic of the area it covers. An enclosed shape that represents areas or surfaces, defined by a series of connected lines forming a closed loop.
The capability of a system to handle a growing amount of work or its potential to accommodate growth. The individual unit in a raster model that holds a value corresponding to the attribute being represented.

 

Distributed Data Storage Real-Time Spatial Data
Stream Processing Frameworks Data Integration
Standardization Performance Bottleneck
Spatial Index

 

Data that changes dynamically over time and has a geographical component, essential for applications like navigation and traffic monitoring. A data storage approach where data is stored across multiple locations, enhancing access speed and reliability.
The process of combining data from different sources into a unified view. Technologies designed to handle continuous flows of data in real-time, improving the management and analysis of rapidly changing information.
A point in the system where the performance is significantly limited or delayed. The act of making data uniform to ensure consistency across different datasets.
A data structure that enhances the performance of spatial queries by organizing spatial data in a way that supports efficient searching.