Data science uses data, statistics, programming and domain knowledge to answer questions, forecast outcomes and support decisions. Useful projects begin with a clear business problem, trustworthy data, a suitable baseline, measurable evaluation and a plan for using the result in
Data analytics often focuses on understanding what happened and why through reporting, queries and analysis. Data science may also build predictive or optimization models. The roles overlap; choose methods based on the decision, data quality and the value of added complexity.
Predictive analytics uses historical data and statistical or machine-learning methods to estimate likely future outcomes, such as churn, demand or lead conversion. Evaluate models against a simple baseline, monitor drift and fairness, and ensure predictions lead to an actionable
Data science uses data, statistics, programming and domain knowledge to answer questions, forecast outcomes and support decisions. Useful projects begin with a clear business problem, trustworthy data, a suitable baseline, measurable evaluation and a plan for using the result in
Data analytics often focuses on understanding what happened and why through reporting, queries and analysis. Data science may also build predictive or optimization models. The roles overlap; choose methods based on the decision, data quality and the value of added complexity.
Predictive analytics uses historical data and statistical or machine-learning methods to estimate likely future outcomes, such as churn, demand or lead conversion. Evaluate models against a simple baseline, monitor drift and fairness, and ensure predictions lead to an actionable