DAAX can deliver several types of projects to its customers. The first step of any undertaking is understanding the business needs and then implementing a solution that meets expectations.

DAAX has established a few basic ground rules when it comes to project management:

  • Team work. We learned a long time ago that success is ultimately achieved through team work. This is reflected in the way our collaborators work together and the way we interact with our customers.
  • Technology.  We are always up to date with state-of-the-art data mining techniques.
  • Success.  We work relentlessly to ensure that every single project we undertake is a success.
  • Communication.  Good communication is at the core of any good business relationship. Our goal is to effectively communicate our methodology, the progress of the work being done and the analyses results.

Overview of projects we undertake.

DAAX manages its projects using the CRISP-DM methodology.  As the pictogram illustrates, we can undertake the management, the development and the implementation of one or several phases of the process.

  • Business understanding. Understanding the business requirement and converting this knowledge into a data mining problem.
  • Data understanding. Collecting initial data and identifying pertinent variables as well as any mitigation plan for those that are problematic.
  • Data preparation. Preparing initial data to be used with modeling tools.
  • Modeling. Selecting the best modeling techniques and developing the data mining model.
  • Evaluation. Auditing and evaluating the developed models and deciding on the final model.
  • Deployment. Creating the final model and implementing the process for optimization of decision making.


Customers are in a position of authority because they are connected more than ever and have constant access to information. Their expectations are higher and their choices are based on positive interactions with your brand. (…)

Predictive maintenance

Predictive maintenance solutions access multiple data sources in real time in order to predict asset failures or quality problems so that your organization can reduce maintenance costs and avoid expensive downtimes. (…)

Risk and fraud

The fraud prevention solution help organizations identify possible fraud issues allowing them to take the necessary measures before losses are incurred. (…)

Threat prevention

Every day, organizations are faced with a multitude of threats. Whether they come from data theft or internal theft, whether dealing with public safety or criminal issues, there is a constant battle to distinguish between acceptable risks and dangerous vulnerabilities. (…)


The recidivism management solution analyzes millions of structured and text data.

The analysis allows optimal treatments to be developed for the inmates during their incarceration so as to help reduce the probabilities of recidivism. (…)

School dropout

Demographical data, test results and disciplinary measures are some examples of variables used to predict the results for certain courses or even the students’ overall performance. This data can then be used to predict the risk of dropping out, the probability of completing a diploma in the expected time or the probability of a student reapplying. (…)