Free IMA CMA Part 1 (Financial Planning, Performance, and Analytics) Technology and Analytics Practice Questions

B is correct. A data lake stores data in its raw, native format (structured tables, semi-structured logs, unstructured documents, images, audio, etc.) and applies a schema only when the data is read for analysis (schema-on-read). This flexibility lets analytics and data-science teams ingest new sources quickly and decide later how to model them.

B is correct. RPA excels at processes that are high-volume, rule-based, repetitive, and operate on structured data from stable interfaces. Intercompany reconciliation fits all four criteria: the rules for matching debits and credits between affiliated entities are deterministic, the source data lives in ledger systems with stable formats, and the volume of transactions makes manual matching tedious. Processes that require judgment, negotiation, strategic framing, or unstructured investigation are poor RPA candidates because the underlying logic cannot be reduced to deterministic rules.

B is correct. The objective combines two distinct requirements. First, identifying customers likely to cancel is a forward-looking probability estimate, which is the definition of predictive analytics: a model is trained on historical churn data to score each active customer's likelihood of cancellation. Second, automatically routing flagged accounts to retention specialists without manual triage is a rule-based, repetitive workflow that is well suited to RPA or a workflow engine. Together, the predictive model produces the signal and the RPA layer executes the action, which is the canonical pattern for technology-enabled finance and operations transformation.