What Type of Systems Generate the Original Source Data for a Data Warehouse?
When it comes to building a data warehouse, one of the most critical steps is identifying and understanding the sources of data. The original source data is the foundation on which the entire data warehouse is built. In this article, we will explore the different types of systems that generate this original source data.
1. Operational Systems
Operational systems are the primary systems that support day-to-day operations within an organization.
These systems include transactional databases, customer relationship management (CRM) software, enterprise resource planning (ERP) systems, and more. Operational systems generate real-time data as various business activities occur.
- Transactional Databases: These databases store transactional information such as sales orders, invoices, customer interactions, and other operational data.
- CRM Software: CRM software tracks customer interactions, manages leads and opportunities, and stores customer-related data.
- ERP Systems: ERP systems integrate various business processes like finance, human resources, inventory management, and supply chain management to provide a holistic view of an organization’s operations.
2. External Data Sources
In addition to internal operational systems, external data sources can also contribute to the original source data for a data warehouse.
These sources can provide valuable insights that complement internal operational data. Here are some examples:
- Social Media Platforms: Social media platforms like Facebook, Twitter, LinkedIn generate vast amounts of user-generated content that can be used for sentiment analysis or market research.
- Data Feeds: Data feeds from external providers can include financial market information or weather data that may be relevant to certain industries.
- Publicly Available Data: Government datasets, public surveys, or industry reports can provide valuable external data for analysis and decision-making.
3. Legacy Systems
Legacy systems refer to older technology systems that are still in use within an organization.
These systems may not have the capabilities to integrate directly with modern data warehousing solutions. However, they often contain valuable historical data that needs to be included in the data warehouse. Extracting and transforming this data from legacy systems is a crucial step in the data warehouse implementation process.
4. Third-Party Applications
Organizations often rely on third-party applications or software as part of their business operations.
These applications may generate their own data that needs to be integrated into the data warehouse. Examples of such applications include customer support ticketing systems, marketing automation platforms, or web analytics tools.
The original source data for a data warehouse comes from various systems within and outside an organization. Operational systems provide real-time transactional data, while external sources bring additional insights from social media platforms, public datasets, and more.
Legacy systems contribute historical data, and third-party applications generate their own unique datasets. Understanding these different types of systems is essential for building a comprehensive and effective data warehouse.