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Just give us your data, and we'll be on our way...
Clearly, this is not our approach to dealing with your valuabe data, and we have a carefully planned process to get from initial contact to the final delivery. In the following, we will outline our process briefly.

A Simplified View of our Data Mining Process

1. Discovery Phase

In the initial phase, we increase our understanding of your business, get to know the people involved, and get a feel for your data. Common activities include:

  • Meeting with the project sponsors and relevant personel
  • Establish the organization's maturity with respect to data, as this determines what can be realised realistically. For example, there may hardly be any data yet, or the data is badly organized, versus an organization which already stores data for long periods and already has Data Mining experience.
  • Assessment of the organization's capability to apply Data Mining techniques. For example, an organization with mainly low-skilled personel will have less opportunities to apply Data Mining than an organization with many academics.

 

Overview of EVIS Data Mining process - click on me for a larger version

2. Entry Phase

Based on the Discovery phase, we now have a realistic feeling of the organization's potential in employing Data Mining. Now it's time to get more concrete and determine the business problem that we need to address. Typical activities include:

  • Defining the business problem (one or more)
  • Defining the stakeholders of the problem, i.e. the people that would benefit from a solution. In addition, we need to determine the people that would oppose the changes, if applicable.
  • Determining the seriousness of the business problem (is it worth solving).
  • Setting an ideal outcome (vision), which can guide us on our path.
  • Preliminary assessment of the feasibility of finding a solution given the domain and available data.

3. Launch Phase

Whereas phase 1 and 2 are mainly setting the environment and determing the feasibility, in phase 3 we move towards a formal project, including

  • Project planning
  • Business problem refinement and specifying the system requirements
  • Determing key project participants
  • Scoping the problem domain: what is included, and what is not.

4. Development Phase

This phase is where the actual Data Mining activities are taking place, and we have to perform:

  • Data validation and cleaning: obtaining data sets, fixing corrupt data, and filling missing data
  • Selection and applying Data Mining algorithms and tools
  • Interpretation and validation of results
  • Presenting the results of the project

5. Infusion Phase

Finally, we need to transfer and infuse the results into your business processes, so you can reap the benefits. This involves:

  • Setting up the Data Mining production environment (moving from development to production)
  • Adjusting your current business process to include the new information
  • Determining your future strategy with respect to Data Mining (specify what data to harvest in the future, how to obtain this data, which data to ignore)

EVIS always tailors this process to a client's specific situation. If you want to know how we could help you, please contact us.