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1. 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.
2. The step where adjustments are made to the model to improve its predictive accuracy and performance.
3. A graph in which edges have a specific direction, indicating relationships between nodes.
4. Queries that involve location-based conditions, enabling the retrieval of data based on spatial relationships and geographic criteria.
5. The process of removing errors and inconsistencies from the collected data before further analysis.
6. The process of inspecting, cleaning, transforming, and modeling data to discover useful information that can support decision-making in business intelligence.
7. 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.
8. The process of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems.
9. A type of data model that represents data as nodes and edges, where nodes are entities and edges are relationships between them.
10. A special type of association in an object-oriented database where one object represents a collection of other related objects.
11. Data that changes dynamically over time and has a geographical component, essential for applications like navigation and traffic monitoring.
12. The process of cleaning, transforming, and organizing data before building a predictive model.
13. A discipline that focuses on the development and design of land use and the built environment.
14. A property or characteristic of a node in a network data model.
15. The first step in the predictive modelling process, involving gathering relevant data from various sources.
16. The process of choosing the most relevant input variables to be used in the predictive model.
17. Dividing a database into segments based on geographic factors such as country, region, or postal code.