What is data warehousing?
A data warehouse pulls in data from sources like POS, CRM, ecommerce and finance systems. The data is organized so it can be queried quickly and compared over time. Teams then analyze it with business intelligence (BI) tools.
How does data warehousing work?
- Data is extracted. Records are pulled from source systems on a schedule.
- Data is transformed. It is cleaned, standardized and matched across sources.
- Data is loaded. The prepared data is stored in structured tables in the warehouse.
- Data is analyzed. Analysts and BI tools query it for reports and dashboards.
Data warehouse vs data lake: what is the difference?
| Data Warehouse | Data Lake | |
|---|---|---|
| Data type | Structured, cleaned data | Raw data in any format |
| Main users | Business analysts and BI tools | Data scientists and engineers |
| Best for | Reporting and trend analysis | Exploration and machine learning |
| Structure applied | Before data is stored | When data is read |
What are examples of data warehousing?
| Venue or Business | Example |
|---|---|
| Retail chain | Sales from every store combined for weekly reports |
| Shopping mall | Foot traffic and tenant sales compared across properties |
| Airport | Passenger, parking and concession data held in one place |
| Hotel group | Bookings, spend and guest feedback analyzed by property |
How do businesses use data warehousing?
- Create one source of truth. Every team reports from the same numbers.
- Compare performance over time. Years of history support trend analysis.
- Combine data across systems. Joining sales, marketing and visit data answers bigger questions.
How does Aislelabs support data warehousing?
Aislelabs data can be exported to BI tools and data warehouses. Aislelabs Flow AI provides anonymous, aggregate foot traffic, dwell time, occupancy and zone data from existing WiFi, so teams can analyze visits alongside their other business data. Explore Aislelabs Flow AI. See also Secure File Transfer Protocol (SFTP).
FAQs
What is the difference between a database and a data warehouse?
A database runs day-to-day transactions. A data warehouse stores history from many systems for analysis.
What is ETL?
Extract, transform, load. It is the process of moving data from source systems into a warehouse.
Are data warehouses in the cloud?
Many are today. Cloud warehouses scale storage and computing as needs grow.
Who uses a data warehouse?
Analysts and finance, marketing and operations teams, often through BI dashboards.
How often is a data warehouse updated?
It depends on the setup. Updates range from daily batches to near real time.
