What is Data
Warehousing?
A data warehouse (DWH) is a repository of an organization’s electronically stored data, extracted from operational systems and made available for ad-hoc queries and scheduled reporting. The data in a data warehouse comes in handy for business analysis and decision-making purposes.
Data warehousing involves extracting, transforming, and loading data from various sources into the data warehouse. This practice typically revolves around hardware, software, and best practices to ensure that the data is accurate, consistent, and accessible to those who need it.
Difference between Data Warehouses and Databases
Often people are confused between data warehouses (DWH) and databases since both share some similarities. So, what distinguishes the two? A database stores current and active data, whereas a data warehouse stores historical data. Additionally, data warehouses are designed for in-depth data analysis, such as reporting, forecasting, and analytics.
Data Warehouse Architecture
A data warehouse architecture uses dimensional models to identify the best technique for extracting meaningful information from raw data and translating it into an easy-to-understand structure. However, you should understand three main types of architecture when designing a business-level real-time data warehouse.
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Single-tier Architecture -
Two-tier Architecture -
Three-tier Architecture
Enlisting the Features
The key features of a data warehouse include
Subject Oriented
It provides information catered to a specific subject area instead of the entire organization’s ongoing operations. Examples of subjects include product information, sales data, customer and supplier details, etc.
Integrated
The integrated version combines data from multiple sources, such as flat files and relational databases, which offers better data visibility and analysis.
Time-Variant
The data in a DWH provides information from a specific historical point in time. Hence, the data is categorized, keeping in view that within a particular timeframe.
Non-volatile
Non-volatile means that historical data is retained and not affected by the addition of new data to the operational database, ensuring that any updates or modifications made are reflected in the data warehouse without impacting the integrity of the existing historical data.
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