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Research question

As explained in Starting Data Analytics with Generative AI and Python

A research question is a specific, answerable question that guides analysis of data in order to address a broader issue.

A research question is a specific, answerable question that translates a broad business concern into an analysis of available data. One business question often requires several research questions. section 3.1

Break broad decisions into questions that analysis can address:

  • Identify who spends the most, whether those customers can buy more, and where similar customers can be found. section 3.1
  • Locate the production step creating the most scrap and determine which parameters could be optimized to reduce it. section 3.1
  • Check whether the available data can support the stakeholder’s desired analysis, such as regional demand prediction or material-ratio optimization. section 3.1

From business concern to research questions

“How do we make more money?” becomes a sequence of narrower questions about customer spending, purchasing capacity, and similar customers. The sequence turns a vague goal into analyzable decisions. section 3.1

How Starting Data Analytics with Generative AI and Python covers it

How deep it goes
Breaks broad questions into multiple data-focused questions but stops short of specifying analytical methods.
Examples
Uses revenue, customer similarity, production scrap, regional demand, and material-ratio questions as concrete examples.
What it assumes
Assumes a defined business goal and familiarity with the contents and availability of relevant data sources.
What you can do after
Apply it to turn a broad stakeholder concern into a sequence of answerable questions.
How it connects
Connects business goals, business stakeholders, data sources, data availability, and data quality.

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This explainer was generated by Manning's knowledge graph from the text of Starting Data Analytics with Generative AI and Python. The section links point to the parts of the book it draws on.