A data warehouse is a data management system specifically designed to facilitate and support businesses with their business intelligence (BI) actions and analytics. Data warehouses handle queries and support analytics and typically contain large quantities of historical information. The data within the data warehouse services are usually drawn from various sources, including transaction applications, log files and external data sources.
It synthesizes and amalgamates huge amounts of data coming from different sources. The analytical potential of data warehousing enables companies and organizations to draw important business insights from their data. Analyzing this improves their decision-making and creates a bulk of historical data that comes in handy for business analytics consulting and data scientists. The inclusive qualities make data warehousing a perfect benchmark for any company to set up before leveraging their data for insights.
Data warehouses deliver a broad spectrum of exclusive benefits, allowing businesses to analyze large quantities of different data, extract substantial value, and maintain historical records. Here are four characteristics that allow data warehousing to give out stunning advantages.
A properly designed data warehouse will have fast query response times, deliver a high volume of data, and allow users to narrow/drill-down & slice, and dice data to meet their analytical needs. It is the foundation for BI (business intelligence) environments that create reports, dashboards, and other interfaces that users can access.
Defining the architecture of a Data Warehouse is key when aligning business goals with technology goals. Each organization has its architecture based on its business needs and requirements. The most common architectural characteristics include: