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1. Processing data in large blocks at scheduled intervals.
2. The process of identifying and capturing changes made to data in real time, enabling real time updates to data warehouses.
3. The analysis of data as soon as it is acquired, often used to make immediate decisions or respond to events as they happen.
4. Where data is processed in small, fixed-size batches rather than processing the data all at once.
5. The process of updating data in a data warehouse as soon as new information becomes available.
6. The process of inspecting, cleaning, transforming, and modeling data to discover useful information that can support decision-making in business intelligence.
7. The process of ensuring the accuracy, completeness, and quality of the extracted and transformed data.
8. 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.
9. The first step in the Extract, Transform, Load (ETL) process, which involves retrieving data from various sources, such as databases, files, or APIs.
10. The process of retrieving or pulling data from the source systems or applications.
11. 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.
12. A central table in a data warehouse that contains the primary measures or metrics of a business process.
13. The delay between data being generated and being available for reporting and analysis in a data warehouse.
14. A smaller, specialized subset of a data warehouse that is focused on a particular business function or department.
15. 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.
16. Using statistical techniques and machine learning algorithms to analyze current and historical data to make predictions about future events and outcomes in business intelligence.
17. A visual display of key performance indicators (KPIs) and other important business metrics, providing a real-time snapshot of the organization's performance.
18. The process of identifying and correcting or removing errors, inconsistencies, and inaccuracies in data stored in the data warehouse.