Business Intelligence (BI) data sources and boundaries Which of the following is NOT a way BI systems obtain or ingest data for analysis and reporting?

Introduction / Context:
Business Intelligence (BI) focuses on turning data into information and insight. A key exam topic is distinguishing BI (analytics, reporting, dashboards, data mining) from OLTP systems (Online Transaction Processing), which capture and record day-to-day business events. This question tests whether you can separate data acquisition methods suitable for BI from operational transaction processing that belongs to OLTP.

Given Data / Assumptions:

• BI systems consume data from various sources to analyze the past and present and sometimes to forecast the future.
• Operational systems (e.g., point-of-sale, order entry) exist to process and record transactions reliably and quickly.
• Organizations may also purchase external datasets to enrich analytics.

Concept / Approach:

BI systems generally read from operational databases, staging areas, or curated warehouses/lakes. They also use batch extracts and third-party data. However, they do not process transactions in the sense of writing order rows, debiting accounts, or updating inventory with ACID guarantees—those are OLTP responsibilities.

Step-by-Step Solution:

Verification / Alternative check:

Enterprise architectures typically separate OLTP and BI/analytics stacks to avoid workload contention and to optimize each for its purpose. BI draws from OLTP but does not replace it.

Why Other Options Are Wrong:

• Read operational DBs: common for reporting or ELT.
• Process extracts: standard ETL/ELT feed.
• Vendor data: widely used to enrich analysis.
• Lake/staging files: a normal analytics intake path.

Common Pitfalls:

• Confusing reading from OLTP with processing transactions.
• Thinking BI must always copy data; some BI reads are virtual or federated.

Final Answer:

Process transactions (capture day-to-day orders, payments, inventory moves).