Real-time Business Intelligence (BI) systems frequently use Stream Processing to capture and process incoming data streams quickly. Stream processing enables real-time analysis and decision-making by handling continuous data flows.

Columnar databases are optimized for analytical workloads, and they store data in columns rather than rows. This allows for better compression because columns often contain more repetitive or identical values, which can be compressed more efficiently.

Cloud-based Data Warehousing Solutions offer organizations increased scalability and flexibility. They allow organizations to scale their data warehousing resources as needed, eliminating the need for heavy on-premises hardware investments. This flexibility is crucial in handling dynamic data requirements and managing costs effectively.

Data normalization is a data transformation technique that involves changing the scale of a variable so that it ranges between 0 and 1. This process is useful for comparing variables with different scales and ensuring that they contribute equally to data analysis and modeling.

Traditional Relational Database Management Systems (RDBMS) are commonly used for Online Transaction Processing (OLTP) applications. OLTP systems are optimized for short, quick transactions, such as order processing or record updates, where data integrity and consistency are paramount.

For capturing daily price changes in a retail database, the most appropriate choice would be SCD Type 2, which allows for the historical tracking of changes to product prices. This type maintains a history of changes, making it ideal for scenarios where you need to preserve historical data. SCD Type 1 overwrites existing data, SCD Type 3 adds new records for changes, and SCD Type 4 is more complex and less commonly used.

Data purging is the process of removing old or obsolete data from the data warehouse to free up storage space. This is essential for maintaining the efficiency and performance of the data warehouse by preventing it from becoming cluttered with outdated information.

Denormalization is a database design technique where data is deliberately duplicated or grouped together to improve query performance. While it may lead to some data redundancy, it can significantly enhance data retrieval speed, making it useful in data warehousing scenarios.

In a typical Business Intelligence (BI) system, components such as data warehouses, data visualization tools, dashboards, and scorecards are integral. However, social media marketing is not a standard component of BI systems.

Risk assessment is a fundamental component of IT risk management. It involves the identification and analysis of potential events or risks that could have adverse effects on the organization. By understanding these risks, organizations can develop strategies to mitigate or respond to them effectively.