Data Science Process: From Business to Delivery

Hany Hossny, PhD
5 min readDec 11, 2022

Data science projects start with business needs and go through data analysis, model development, deployment to production, quality assurance, and after-deployment support. The image below illustrates the key steps and actions included in each step during the life cycle.

Data Science Process from Business to Delivery

The Deliverables

Data Science Deliverables

Along the development life cycle, each project can deliver multiple deliverables according to the business need, as listed below.

  1. Descriptive reports, including statistical analysis, correlation analysis reports, and descriptive dashboards.
  2. Predictive model, including the model APIs, features importances, sensitivity analysis reports, and what-if dashboards.
  3. Prescriptive models include optimisation processes and prescribing the best values for the predictor variables that maximise the value of the target variable.

Development Process

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Hany Hossny, PhD
Hany Hossny, PhD

Written by Hany Hossny, PhD

An AI/ML enthusiast, academic researcher, and lead scientist @ Catch.com.au Australia. I like to make sense of data and help businesses to be data-driven

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