Business Process Optimization

Application Areas: Data Mining, Market Feed Processing, Resource Scheduling, Text Classification

Today, many businesses have workflows that require technology beyond standard enterprise solutions. This can involve applications that operate on very large datasets, for example data mining large databases, or that are very computationally intensive, for example performing statistical modeling or process simulations.

Challenge
Provide the performance required for critical workflows within constrained power envelopes and server footprints.

Mitrion Solutions
Within the field of data mining several analyses methods have potential for MVP acceleration. Data mining software analyzes relationships and patterns in stored transaction data based on open-ended user queries. Generally, any of four types of relationships are sought:

Classes: Stored data is used to locate data in predetermined groups.
Clusters: Data items are grouped according to logical relationships or consumer preferences
Associations: Data can be mined to identify associations. 
Sequential patterns: Data is mined to anticipate behavior patterns and trends.

The data mining analysis methods that show most promise for MVP acceleration are:

Artificial neural networks - Non-linear predictive models that learn through training and resemble biological neural networks in structure.
Genetic algorithms - Optimization techniques that use processes such as genetic combination, mutation, and natural selection in a design based on the concepts of natural evolution.
Decision trees - Tree-shaped structures that represent sets of decisions. These decisions generate rules for the classification of a dataset.
Nearest neighbor method - A technique that classifies each record in a dataset based on a combination of the classes of the k record(s) most similar to it in a historical dataset (where k 1). Sometimes called the k-nearest neighbor technique.
Rule induction - The extraction of useful if-then rules from data based on statistical significance.
Data visualization - The visual interpretation of complex relationships in multidimensional data.