What is Activity Data?
Activity data refers to the data created or modified during the execution of a business activity—typically within a transactional application such as ERP, CRM, or supply chain systems. It represents the real-time, operational output of an event or task being performed in a system.
Key Characteristics of Activity Data-
- Transactional Nature:
Activity data is directly tied to a business transaction, such as processing an order, updating inventory, submitting a time sheet, or recording a payment. - Exclusive Write Access:
- Only one user or process has the right to write or update the data at a time.
- This prevents data conflicts and ensures consistency and integrity in a transactional environment.
- Short-Term Relevance:
Activity data is usually ephemeral—its primary purpose is to support the current transaction. Once the transaction is completed, the data may be archived, aggregated, or transformed into longer-term reference or master data. - High Volume, High Velocity:
In active systems, activity data can be generated at a rapid pace and in large volumes—especially in industries like e-commerce, banking, or logistics. - Application-Centric:
It is closely tied to the application layer, generated during interactions with business logic, user interfaces, APIs, or automated workflows.
Examples of Activity Data
Business Activity | Activity Data Generated |
---|---|
Customer places an order | Order ID, timestamp, product ID, quantity, price |
Employee clocks in | Time entry, employee ID, location |
Shipment is processed | Shipping label ID, tracking number, status |
Payment is recorded | Transaction ID, amount, method, confirmation code |
Activity Data vs. Other Data Types
Data Type | Description |
---|---|
Activity Data | Operational data created during transactions; often volatile and real-time |
Master Data | Core business entities (e.g. customer, product) with a long life cycle |
Reference Data | Fixed values used for categorization (e.g. country codes, tax types) |
Analytical Data | Aggregated and processed data used for reporting and insights |
Usage in Systems
- Transactional databases (e.g., OLTP systems)
- Workflow engines that log activity as part of process automation
- Audit trails or logs for traceability
- Event-driven architectures where each activity creates events and data flows