A retail company uses Adobe RT-CDP to ingest transactional data from its POS system daily and web browsing behavior in real time. What is the best data ingestion strategy?

Question

Options

• AUse batch ingestion for POS data and Edge ingestion for web browsing behavior.
• BStream both POS data and web behavior to reduce latency.
• CBatch process both POS data and web behavior for consistency.
• DExport web browsing data to an external identity graph.

• A
  74% (14)
• B
  5% (1)
• C
  5% (1)
• D
  16% (3)

Explanation

Option A matches the data's natural cadence to the right ingestion method. POS transactional data arrives in discrete daily batches, so batch ingestion is appropriate - it's efficient, cost-effective, and the slight delay is acceptable for historical analysis. Web browsing behavior, however, drives real-time personalization (think product recommendations, abandoned cart triggers), so Edge ingestion - which processes data at or near the source with minimal latency - is the correct fit for that stream.

Why the distractors fail:

• B is wasteful: streaming POS data adds unnecessary complexity and cost when daily batch processing meets the business need.
• C batching web behavior defeats the purpose of RT-CDP; stale browsing data can't power real-time personalization.
• D is a red herring - exporting to an external identity graph is an identity resolution strategy, not a data ingestion strategy, and doesn't address the core question.

Memory tip: Match ingestion method to data urgency - "If it can wait, batch it; if it can't, edge it." POS data closes at end of day (can wait), browsing behavior expires in seconds (can't wait).

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