In information systems, which description best matches an operational system (OLTP)—that is, the system used to run the business day-to-day?

Introduction / Context:
Operational (OLTP) systems handle daily transactions—orders, payments, inventory updates—requiring immediate consistency and quick response times. Distinguishing OLTP from analytical (OLAP) systems is foundational for data architecture.

Given Data / Assumptions:

• Operational systems support current, transactional workloads.
• Analytical systems support historical trend analysis and decision making.
• Real-time or near-real-time writes occur in OLTP systems.

Concept / Approach:
OLTP systems emphasize current data, concurrency control, and transactional integrity (ACID). In contrast, data warehouses and OLAP cubes use historical, integrated data for analysis and reporting. The correct identification focuses on “run the business” and “current data.”

Step-by-Step Solution:

Verification / Alternative check:
Classic OLTP vs. OLAP definitions: OLTP = current, write-intensive; OLAP = historical, read-intensive, analytical.

Why Other Options Are Wrong:
Historical data: That is data warehousing/OLAP.
Decision making: Also OLAP/BI, not day-to-day operations.

Common Pitfalls:
Confusing “near real-time reporting” from a warehouse with OLTP; warehouses can be refreshed frequently but remain analytical.

Final Answer:
A system that runs the business in real time and is based on current data.