Data Translation is a four-stage framework for turning a defined business question and the raw data you actually have into an analysis-ready field set, without inventing evidence the data does not contain.
Use it to identify available raw fields, sort them by analytical role, translate business concepts into fields that can be used directly, derived or flagged as missing, and check whether the finished field set is ready for analysis.
The framework is designed for business, growth, revenue and operating questions where the data rarely arrives perfectly structured for the question you need to answer.
How to use it
Identify the raw data you actually have access to.
Sort each field by the role it may play in the analysis.
Translate the business concepts in the question into fields you can use directly, derive or flag as missing.
Check whether the finished field set can evaluate the question honestly.
Move forward when the field set is Ready for Analysis or Ready with Known Limitations. If a critical part of the question cannot be represented, return to the question and narrow or reframe it before analysis begins.
This board can be used on its own, or as part of Signal Foundry’s Commercial Investigation System:
TRACE: Frame the business question worth investigating.
Data Translation: Turn the question into analysis-ready data.
SLICE: Analyze the data to find meaningful patterns. (board coming soon)
SIGNAL: Qualify findings into evidence-backed implications. (board oming soon)
