What is Data Warehouse?
Turkish: Veri Ambarı
A data warehouse stores cleaned, structured data from multiple sources for analytics queries, KPI tracking, and business reporting.
What is a Data Warehouse?
A data warehouse is a central store where data from operational systems is cleaned, modeled, and made queryable for analysis and reporting. Its purpose is not to run daily transactions; it makes historical data comparable and fast to analyze.
A business may keep sales, inventory, accounting, advertising, and customer support data in separate systems. A data warehouse brings those sources together around shared date, customer, product, and channel dimensions so management reports rely on the same reality.
How Does It Work?
Data is usually moved into a warehouse through ETL or ELT processes. Source records are cleaned, duplicates are resolved, fields such as dates and currencies are standardized, and the result is modeled into analytical structures such as fact and dimension tables.
Common modeling approaches include:
- Star schema: A central fact table surrounded by dimension tables
- Snowflake schema: More normalized dimension structures
- Data mart: A department-specific subset for sales, finance, or marketing
- OLAP: A multidimensional approach for fast aggregation and analysis
Business Use
Data warehouses support financial reporting, sales performance analysis, inventory planning, customer segmentation, and executive dashboards. BI tools often connect to the warehouse so teams can examine the same metrics across different dimensions.
A data lake is more flexible and raw-data oriented, while a warehouse is more controlled, defined, and reporting oriented. Successful warehouse projects depend as much on metric definitions, data quality, and refresh schedules as on table design.
Related Terms
BI turns company data into reports, dashboards, and analysis models that make decision-making processes visible.
Data PipelineA data pipeline collects, cleans, transforms, and moves data from sources to a target system for reporting or analytics.
ETL (Extract, Transform, Load)ETL extracts data from multiple sources, transforms it, and loads it into a data warehouse or reporting system on a schedule.
Master Data ManagementMaster Data Management governs critical customer, product, and supplier records through a single source, quality rules, and approvals.
OLAP (Online Analytical Processing)OLAP is a data processing approach optimized for multidimensional analysis, used in business intelligence and reporting systems.
Business ReportingBusiness reporting turns operational, sales, finance, or inventory data into recurring metrics and views that support day-to-day decisions.