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#Data analysis#Project workflow#Business improvement

A Typical Business Data Analysis Workflow

Oct 13, 2026 1 min read

A visual overview of business data analysis, from goal setting and existing-data assessment to preparation, exploratory analysis, reporting, and improvement evaluation.

A typical business data analysis project can be organized into four phases and eleven steps, with iteration between phases as the questions and available data evolve.

A typical business data analysis workflow: define goals, understand the business, assess metrics and data, prepare and explore data, communicate findings, pilot changes, evaluate, and monitor.

Open the full workflow diagram

Four phases

  • Understand the business (①–③): Define the problem and success criteria, understand the business context, agree on metric definitions, and assess existing data.
  • Prepare the data (④–⑥): Reuse business data and add collection where needed; integrate, clean, validate, and reconcile records with SQL/Python.
  • Analyze and communicate (⑦–⑧): Explore segments and trends, use statistical methods where appropriate, and visualize and communicate validated conclusions with tools such as Tableau/BI.
  • Improve and evaluate (⑨–⑪): Design changes and evaluation methods before piloting, run A/B tests where suitable, decide rollout from the results, and continue monitoring and iterating.

References: CRISP-DM · NIST exploratory data analysis · Microsoft experimentation practices. This is a simplified overview adapted to business analytics.

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