Difference Between Data Mining & OLAP in Tabular Form.
| SNO. | Data Mining | OLAP |
| 1. | It is used to predict the future. | OLAP is used to analyze the past. |
| 2. | Prepare data, launch mining tool and sit back. | Multidimensional, drill-down and slice-and-dice. |
| 3. | lt has large number of dimensions. | lt has limited number of dimensions. |
| 4. | lt deals with summary of data. | lt deals with ‘detailed transaction level data. |
| 5. | It is stiu emerging | Mature and widely used. |
| 6. | Insight and predication | Analysis |
| 7. | Data Mining : Multidimensional analysis. | OLAP : Online Analytic Processing |
| 8. | Bottom-up, discovery-driven | Top-down, query-driven |
OLAP summarizes data and makes forecasts. For example, OLAP answers questions like “What are the average sales of mutual funds, by region and by year?”
Data mining discovers hidden patterns in data. Data mining operates at a detail level instead of a summary level. Data mining answers questions like “Who is likely to buy a mutual fund in the next six months, and what are the characteristics of these likely buyers?”
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