What is real-time data warehousing?

Overview

The fusion of real-time activity and data warehousing is called real-time warehousing. The business activity data is captured in a real-time data warehouse as the data arises.

Real-time data warehousing is used as an information retrieval framework as soon as the data becomes available.

In real-time data warehousing, the warehouse updates each time the system executes a transaction. It means that when a query triggers in the warehouse, it will return the company's status at that time.

Benefits of real-time data warehousing

Real-time data warehousing has many advantages, including:

• It makes faster decisions based on more up-to-date, accurate, and transactionally consistent data.
• It reduces the load on the data source. Many organizations struggle to identify the perfect data loading window due to low-impact log-based change data capture (CDC).
• It accelerates recovery from data conversion or load issues.
• It removes the batch window that needs to idle the source database and possibly the data warehouse during loading. It prevents inconsistent data from being reflected in the query.
• It allows the advantage of robust data warehousing or data martIt is a subject-oriented database which is a segment of an enterprise data warehouse. databases by running hierarchies in databases rather than in a separate runtime environment.

Data warehousing vs. real-time data warehousing

Traditional data warehouses consist of an integrated collection of historical data used to make strategic decisions across the enterprise. It consolidates various independent data sources to create a personal view of your organization.

Real-time data warehousing keeps up with the growing demand for up-to-date information by updating stored data daily. Therefore, the information stored in the real-time data warehouse helps to understand the actual situation of the organization better when the data is queried and analyzed.

Here are some more critical differences between them: