> For the complete documentation index, see [llms.txt](https://gchandra.gitbook.io/data-warehousing/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://gchandra.gitbook.io/data-warehousing/fundamentals/what-is-a-data-warehouse/problem-statement.md).

# Problem Statement

RetailWorld uses different systems for sales transactions, inventory management, customer relationship management (CRM), and human resources (HR). Each system generates a vast amount of data daily.

The company's management wants to make data-driven decisions to improve its operations, optimize its supply chain, and enhance customer satisfaction. However, they face the following challenges:

1. **Data Silos**: Data is stored in separate systems, making gathering and analyzing information from multiple sources challenging.
2. **Inconsistent Data**: Different systems use varying data formats, making it hard to consolidate and standardize the data for analysis.
3. **Slow Query Performance**: As the volume of data grows, querying the operational databases directly becomes slower and impacts the performance of the transactional systems.
4. **Limited Historical Data**: Operational databases are optimized for current transactions, making storing and analyzing historical data challenging.

**Solution**

1. **Centralized Data Repository**: The Data Warehouse consolidates data from multiple sources, breaking down data silos and enabling a unified view of the company's information.
2. **Consistent Data Format**: Data is cleaned, transformed, and standardized to ensure consistency and accuracy across the organization.
3. **Improved Query Performance**: The Data Warehouse is optimized for analytical processing, allowing faster query performance without impacting the operational systems.
4. **Historical Data Storage**: The Data Warehouse can store and manage large volumes of historical data, enabling trend analysis and long-term decision-making.
5. **Enhanced Reporting and Analysis**: The Data Warehouse simplifies the process of generating reports and conducting in-depth analyses, providing insights into sales trends, customer preferences, inventory levels, and employee performance.