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Business Intelligence vs Data Science
Business Intelligence (BI) and Data Science are often confused because both work with organisational data, but they answer different kinds of questions using different techniques.
Business Intelligence
BI focuses on reporting and monitoring - it answers "what happened?" using dashboards, KPIs, and historical reports, typically built on structured data with tools like Power BI or Tableau.
Data Science
Data Science goes further, focusing on "why did it happen?" and "what will happen next?" using statistical modeling, machine learning, and often less structured data such as text, images, or logs.
Side by Side Comparison
| Aspect | Business Intelligence | Data Science |
|---|---|---|
| Main Question | What happened? | Why, and what's next? |
| Typical Output | Dashboards and reports | Predictive models |
| Data Type | Mostly structured | Structured and unstructured |
| Common Tools | Power BI, Tableau, SQL | Python, R, ML libraries |
The two fields complement each other rather than compete - many organisations use BI dashboards for day-to-day monitoring and rely on Data Science for deeper, forward-looking analysis.
Coming Up Next
Next, you'll walk through the typical life cycle followed in a Data Science project.