Business Data Warehousing - Module 2

These flashcards cover key concepts in business data warehousing, differentiating between types of data systems, methodologies, data characteristics, and the roles of data warehouses in organizational decision-making.

Data Warehouse (DW)

A central data repository used for reporting and data analysis, integrating multiple data sources.

Business Data Warehouse (BDW)

Centralized system for collecting, storing, and managing data to support decision-making.

Online Transaction Processing (OLTP)

System designed for managing transaction-oriented applications, focusing on efficiency and speed in handling daily operations.

Online Analytical Processing (OLAP)

System used for analyzing large volumes of data, characterized by complex queries and data analysis.

ETL (Extract, Transform, Load)

Process for preparing data for analysis by extracting from sources, transforming into suitable formats, and loading into a data warehouse.

Subject-Oriented

Data organized around specific subjects, such as sales or customer information, rather than specific applications.

Time-Variant

Data that is stored with a specific time context, allowing for historical data analysis.

Non-volatile

Refers to data that is permanent and can only be refreshed, not updated or deleted.

Bill Inmon

Known as the 'father of data warehousing', he advocated a top-down method for designing data warehouses.

Ralph Kimball

Proposed a bottom-up approach for data warehouse design, emphasizing the use of data marts.

Operational Data Store (ODS)

A central database used for operational reporting, complementing the enterprise data warehouse by storing current data.

Data Mart

A subset of a data warehouse tailored for the specific needs of a particular department or business line.

Data Silos

Isolated data sources that are not adequately integrated, leading to inconsistent data across an organization.

Cloud Computing

Technology that allows data warehousing solutions to be hosted on cloud platforms, providing scalability and flexibility.

Data Integration

The process of combining data from different sources to provide a unified view.

Single Source of Truth

A data management concept where a single data source is utilized to provide a consistent and accurate representation of data.

Historical Data

Data collected from past events used for analysis and decision-making.

Real-Time Analytics

The use of data and related resources as soon as they are available, offering up-to-date insights.

Data Quality

Refers to the accuracy, consistency, and reliability of data.

Data Governance

Policies and practices ensuring the management of data availability, usability, integrity, and security.