Imagine the amount of data recorded in a mall on average, just based on #transactionaldata. Each time a customer makes a purchase, a transaction is recorded, capturing details such as items bought, prices, the payment method, location of the sale, and more.
“Transactional data refers to the information generated during the execution of business transactions or interactions. It captures the specific details of each transaction, including the date, time, parties involved, products or services exchanged, and financial aspects.”
Transactional data types include:
- Order line status data type (OL)
- Transaction log data type (TLOG)
- Inventory availability data type (INV)
- Replenishment data type (REPL)
- Markdown candidate data type (MKC)
Transactional data plays a crucial role in sales analysis, inventory management, customer behavior, and financial reporting. By analyzing patterns and trends within transactional data, organizations can identify popular products, optimize inventory levels, and personalize customer experiences.
Transactional data is often stored in transactional databases or enterprise resource planning (ERP) systems, ensuring data integrity, security, and accessibility. With the advancement of big data technologies and analytics, organizations can leverage transactional data to uncover hidden opportunities, enhance operational efficiency, and gain a competitive edge.
By analyzing this data, organizations can optimize their operations, improve customer experiences, and make data-driven decisions.