Modern Database Management Chapter 10 – Data Quality and Integration – Flashcards

High-level organizational groups and processes that oversee data stewardship across the organization. It usually guides data quality initiatives, data architecture, data integration and master data management, data warehousing and business intelligence, and other data-related matters.

A person assigned the responsibility of ensuring that organizational applications properly support the organization's enterprise goals for data quality.

Disciplines, technologies, and methods used to ensure the currency, meaning, and quality of reference data within and across various subject areas.

Technique that indicates which data have changed since the last data integration activity.

A technique for data integration that provides a virtual view of integrated data without actually creating one centralized database.

A method of capturing a snapshot of the required source data at a point in time.

A method of capturing only the changes that have occurred in the source data since the last capture.

A process of using pattern recognition and other artificial intelligence techniques to upgrade the quality of raw data before transforming and moving the data to the data warehouse. Also called data cleansing.

An approach to filling a data warehouse that involves bulk rewriting of the target data at periodic intervals.

An approach to filling a data warehouse in which only changes in the source data are written to the data warehouse.

The component of data reconciliation that converts data from the format of the source operational systems to the format of the enterprise data warehouse.

The process of partioning data according to predefined criteria.

The process of combining data from various sources into a single table or view.

The process of transforming data from a detailed level to a summary level.