TECHNOLOGY

TECHNICAL ASPECT

Data mining is the process of extracting patterns from data. Data mining is seen as an increasingly important tool by modern business to transform data into business and process intelligence from large databases. Data Mining uses a broad range of tools from statistics, automatic learning, pattern recognition, database technologies, visualization and artificial intelligence. This mix of technologies is the core of the PEPITo® platform, the Data Mining software developed by PEPITe.

METHODOLOGY

In addition, Data Mining needs to be regarded as a process. PEPITe follows the CRISP-DM standard (CRoss Industry Standard Process for Data Mining). CRISP-DM is the industry standard methodology for data mining and predictive analytics and has been developed by a industry consortium. This methodology makes large data mining projects faster, cheaper, more reliable and more manageable.

INDUSTRIAL APPLICATIONS OF DATA MINING

Today, the complexity of modern industrial processes in a highly competitive environment has forced industry to invest heavily in automation and monitoring systems. These new installations are generating large databases of data that are often not fully exploited. At the same time there is an increase in interest and efforts regarding continuous improvement following different management standards such as Six Sigma, ISO9000 etc. These standards are encouraging learning from history, by analyzing historical data, as an input to the continuous improvement process. Data Mining plays an important role in the continuous improvement of industrial processes.

THE INFORMATION LIFECYCLE

This is part of a continuous improvement process where the decision is the driver

• Depending on the decision that needs to be taken, certain measurements are needed.
• The values of these measurement needs to be stored, cleaned and organized.
• Once these values has been cleaned and organized, it is possible to analyze these values in order to extract some knowledge.
• When the knowledge has been extracted, it is possible to take an informed decision and take action.

As this is a cycle it is possible to start small and to continuously improve the information cycle.