Decision Analysis Software

Decision making software is a tool intended to support the decision making process but not to replace it. The software frees decision makers from the technical details of the decision-making method employed and makes it possible for them to focus on fundamental value judgments.

A large number of software packages are available. Their quality and price is extremely variable. Some of the packages are exorbitantly expensive. Some are less expensive and even free but nevertheless of high quality. I have selected the following packages for my own use:

TreeAge Pro
Analytica Free

These packages may be shortly characterized as follows:

TreeAge Pro is a visual modeling tool for building and analyzing decision trees, influence diagrams and Markov models. It employs Bayes analysis and multicriteria decision making.

AgenaRisk uses the latest developments from the field of artificial intelligence and visualisation to solve complex, risky problems. AgenaRisk enables decision-makers to measure and compare different risks in a way that is repeatable and auditable. The AgenaRisk solution includes predictive analytics and scales up to organisational-level risk monitoring and assessment. It is ideal for risk scenario planning.

1000minds is an online decision-making software for multi-criteria decision making. The software implements the “potentially all pairwise rankings of possible alternatives (PAPRIKA) method.

Analytica is a visual decision-making software. It combines hierarchical influence diagrams for visual creation and view of models, arrays folr working with multidimensional data, Monte Carlo simulation, for analyzing risk and uncertainty, and optimization, including linear and nonlinear programming.

PriEsT is an open-sources decision making software that implements the analytic hierarchy process method.

Decision Analysis Software – Page

Data Analysis Software

The recent tidal wave of data has given rise to the development of a large number of software programs relevant to the analysis of the data. From a long list of programs I have chosen the following for my own use:

  1. Tableau
  2. DataDesk
  3. StatCrunch
  4. BestView – Addon to Mathematica
  5. Mathematica
  6. R
  7. ParallAX
  8. NeuroSolutions
  9. Gephi
  10. Ayasdi

Some of these programs are preexisting programs that have been adapted to the requirements of big data, some are new, as for example Tableau and Ayasdi. The programs I have chosen are not necessarily the best for all but they are the best for my present needs.

Data Analysis Software – Page

Decision Analysis

Decision Analysis is a systematic, quantitative and visual approach to addressing and evaluating important choices confronted by decision makers. Decision analysis utilizes a variety of tools to evaluate all relevant information to aid in the decision making process.

From <>

After all of the alternatives have been analyzed and a final decision has been reached, there are steps that should be taken during the implementation process for that decision. Three essential actions to implementing a decision include creating an implementation plan, informing stakeholders, and finally, adjusting the decision to make compromises as necessary.


Decision Analysis – Page

Books about Data Analysis

In order to become proficient in data analysis it is necessary to study the theory and practice of data analysis,

A large number of books have been written about data analysis, especially after the data deluge in recent years and the appearance of relatively inexpensive and effective data analysis software.

I have read or at least skimmed through a considerable number of these books and am keeping them on hand as reference books when I work  on data analysis projects.

A list of these books can be found in the page Data Analysis Books

From these books I have learned that data analysis is a process consisting of a sequence of stages beginning with  data and ending in knowledge derived from the information in the data.

This knowledge may then be used in making decisions and implementing them by corresponding actions.

The books place different emphasis on the different steps in the data analytic process. Some emphasize the data end, some the analytic middle, some the visualization of the data and the results of the analysis.

The quality of the books are is quite varied. All of them contain something of value and can be used for reference. Some of them I find of special interest to me and have selected for thorough reading. These are:

      1. Data Just Right – Manoochehri
      2. Making Sense of Data – Myatt
      3. The Visual Display of Quantitative Information – Tufte
      4. Visual Statistics – Seeing Data with Dynamic Interactive Graphics – Young et alia
      5. Tableau Your Data – Murray
      6. DataDesk Manual
      7. Parallel Coordinates – Inselberg
      8. Modeling Techniques in Predictive Analytics – Miller
      9. Predictive Analytics for Dummies – Bari, Chaouchi, Jung
      10. R for Dummies – Meys, de Vries

These books are not necessarily the best for all but they are the best for fulfilling my present needs.

Data Analysis Books – Page