The tools and technologies available to business continue to grow. Many technologies have been developed over time; these have subsequently been used to leverage corporate databases. Data mining is another step along that path. Pilot Software explains the path of evolution using a table similar to the one below [3]:
| Evolutionary Step | Business Question | Enabling Technologies | Product Providers | Characteristics |
| Data collection (1960s) | "What was my total revenue in the past five years?" | Computers, tapes, disks | IBM, CDC | Retrospective, static data delivery |
| Data access (1980s) | "What were the unit sales in Ontario last month?" | Relational databases (RDBMSes), SQL, ODBC | Oracle, Sybase, Informix, IBM, Microsoft | Retrospective, dynamic data delivery at record level |
| Data Warehousing and Decision Support (1990s) | "What were the unit sales in Canada last month? Drill down to Vancouver." | On-line analytical processing (OLAP), multidimensional databases, data warehouses | Pilot, Comshare, Arbor, Cognos, Microstrategy | Retrospective, dynamic data delivery at multiple levels. |
| Data Mining (emerging today) | "What's likely to happen to Vancouver unit sales next month? Why?" | Advanced algorithms, multiprocessor computers, massive databases | Pilot, Lockheed, IBM, SGI, numerous startups (nascent industry) | Prospective, proactive information delivery. |
Data mining is slowly gaining acceptance as a indispensable tool in the business world. Gerber reports that data mining is still in its infancy (and so care should be required in its use), but that it is a useful tool. [5] In time, data mining usage in production information systems will increase.