TechFinity develops and implements complex system solutions by identifying the key aspects and requirements associated with the ‘three legs’ of complex problem domains, which include:
- Large Scale Analysis / Big Data
- Decision Support
- Resource Allocation
Large Scale Analysis / Big Data
Managing and analyzing large sets of data is an increasingly important function in complex system solutions. This problem area presents a number of challenging characteristics, including:
- Significant increases in the volume of data and information
- Data generation by multiple, heterogeneous sources
- Disparities between data types and data sets of related information
The primary objective of large scale analysis is to generate an integrated view of a situation.
Accomplishing this objective can require sophisticated analyses such as:
- Data correlation techniques
- Data fusion techniques
- Identification of patterns and relationships
Decision support is another critical function in complex systems. While large scale analysis is focused on correlating and combining data and information, decision support consists of analyses that examine the impact or effect of the options or course of actions that are presented from an analysis of data.
Decision support analyses, in a general sense, try to make the following assessments:
- Effectiveness of a particular interaction
- Assessment of risk or other effect
In complex systems the decision support analyses often are applied to predict future events or conditions, or to approximate effects based on limited information, so the analysis techniques are often probabilistic in nature.
Resource allocation addresses the fundamental issue of how to balance the best options for a specific decision or course of action against the objectives and constraints of an overall system objective. Making the obvious ‘best choice’ on a case-by-case basis often does not result in an optimal solution for a complex system.
Resource allocation tries to optimize the overall performance or effectiveness by considering the following inputs and requirements:
- Data analysis and decision support data
- System constraints
- System level or mission objectives
Constraints of the application domain also impact what techniques and algorithms can be effectively utilized to solve a resource allocation problem.
Some examples include:
- Optimal versus near-optimal solutions
- Approximation methods
- Real-time computational requirement
- Performance versus cost