Title: Data Warehouse Author: Kriko Published: May 23, 2023 Last modified: Jul 11, 2026 --- 1. [Home](https://kriko.io/) / 2. [Glossary](https://kriko.io/glossary) / 3. D Letter # Data Warehouse A **[data](https://kriko.io/services/data-analysis-insight) warehouse**, commonly abbreviated as DWH, is a [data](https://kriko.io/services/data-analysis-insight) management system that brings information from different sources together for analysis and reporting. Companies and institutions can use [data](https://kriko.io/services/data-analysis-insight) warehouses to evaluate information from areas such as sales, finance, operations and customer relationship management within a shared structure. This helps organisations assess historical performance, understand current conditions and make more informed decisions. [Data](https://kriko.io/services/data-analysis-insight) warehouses are widely used in business intelligence, reporting and strategic analysis processes. Information from databases, operational systems, applications and external sources is combined within a [data](https://kriko.io/services/data-analysis-insight) warehouse according to defined rules. Before the information becomes suitable for analysis, it may be cleansed, transformed and standardised. [Data](https://kriko.io/services/data-analysis-insight) held in different formats across separate systems can therefore be converted into a more consistent structure. This reduces the risk of the same metric being calculated differently across departments. One of the main advantages of a [data](https://kriko.io/services/data-analysis-insight) warehouse is its ability to store long-term historical information. Operational systems are designed to manage daily transactions, while [data](https://kriko.io/services/data-analysis-insight) warehouses are structured primarily for analysis, comparison and reporting. Current and historical information can be evaluated together, making period-based changes easier to examine. For example, a company may compare sales performance, customer behaviour or inventory movements over the last five years through its [data](https://kriko.io/services/data-analysis-insight) warehouse. [Data](https://kriko.io/services/data-analysis-insight) warehouses can be used in industries such as banking, retail, insurance, manufacturing, energy, public services and e-commerce. They can support risk analysis, customer segmentation, financial reporting, campaign performance measurement and operational efficiency analysis. Organisations may build their own data warehouse infrastructure or use cloud-based data warehouse services. Cloud solutions can offer scalability and faster deployment, but security, cost and data governance requirements must be evaluated carefully. A data warehouse architecture is commonly described through three main layers. In the lower layer, information from source systems is collected, cleaned and transferred into the target structure through ETL or ELT processes. In the middle layer, data is stored, modelled and prepared for analysis. In the upper layer, users access the information through reporting tools, business intelligence platforms and query interfaces. Data engineers, data warehouse specialists, business analysts and BI teams may work together in data warehouse processes. Data engineers design data flows and integration processes, while business analysts and BI specialists define reporting and analytical requirements. Analysts can use warehouse data to prepare performance reports, dashboards and decision-support analyses. A well-designed **data warehouse** helps organisations use their information in a more reliable, consistent and strategic way. ## Discover it in the dictionary ### Turkish Electronic Commerce Law The Electronic Commerce Law, officially known as Law No. 6563 on the Regulation of Electronic Commerce, is the main law that regulates the fundamental… ### Customer Journey Map A Customer Journey Map is an analytical tool that visually and systematically shows all the stages in which a customer interacts with a brand,… ### Pareto Principle (80/20 Rule) The Pareto Principle, also known as the 80/20 rule, is an observation and prioritization approach suggesting that a large share of outcomes often comes… ### Dropshipping Dropshipping is a sales and order fulfilment model in which an e-commerce business sells products without keeping them in its own warehouse and instead… ### Data Virtualization Data virtualization is a data management approach that enables users to access information stored across different sources without physically transferring it into a single… ### Technical SEO Technical SEO refers to the technical optimization work that helps a website be crawled, understood, indexed and experienced more effectively by search engines and… ### Google Tag Manager (GTM) Google Tag Manager, commonly abbreviated as GTM, is a free tag management system that allows marketing, analytics and measurement tags used on websites or… ### Information Processing Cycle The information processing cycle refers to the stages through which raw data is transformed into meaningful information. During this process, data is entered into… ### Apache Hive Apache Hive is an open-source data warehouse system used to query, process and analyse large datasets. Developed as part of the Apache Hadoop ecosystem,… ## Track the digital heartbeat with Kriko Subscribe to receive curated insights, news, and ideas shaping the digital landscape. By checking this box, you acknowledge and accept our [privacy policy](https://kriko.io/privacy-policy).