Companies have large data volumes from different sources at their fingertips. However, they can only make full use of the data if they are able to identify connections relevant to their business. This is where data mining starts.
Data mining is typically used for customer segmentation, sales controlling, and target marketing. Its objective is to identify trends and patterns in existing data sources. These are usually based on sophisticated mathematical procedures, which can only be analyzed and interpreted by experts.
However, a company’s daily business requires fast and versatile solutions. Departments need to be able to answer any questions as fast as possible.
Consolidated analyses and the reconciliation of different data sources present a major challenge to companies. High data quality is a key factor here. Decisions can only be based on revealed connections, patterns and trends if the underlying data are reliable.
The success of a data mining tool hinges on the following question:
How can large data volumes from different IT systems be cleansed and provided so that any specialist can make full use of them to gain new insights?