Databases Reference
In-Depth Information
roles, risks, milestones as well as estimating costs, benefits, taking into ac-
count the cross-dependant nature of all the elements. Efforts presented in
Sect. 2 towards a methodology have generated a “good manners” guide as
well as a definition of the technical activities to be developed in the process
of knowledge discovery. However, no clear result towards the management of
the global process have been obtained up to date. Higher risk levels, greater
efforts and higher associated costs with each task being developed is the result
of a lack of understanding of the project development process due mainly to a
lack of methodology. Methodologies make the development team concentrate
their efforts in tasks to be developed, clearly defining roles and assignment for
each participant making organization and project development a lot easier.
Consequently, prior to defining the methodology, the terms we are refereing
to have to be clearly understood and defined.
A project has been defined as any piece of work that is undertaken or
attempted. Consequently, project management involves “the application of
knowledge, skills, tools and techniques to a broad range of activities to meet
the requirements of the particular project” [3]. Project management is needed
to organize the process of development and to produce a project plan. The
way the process is going to be developed (life cycle) and how it will be split
into phases and tasks (process model), will be established. This project defin-
ition [23] exactly describes the common understanding, its extent and nature,
among the key people involved in a project. Thus, any data mining project
need to be defined to state the parties, goals, data and human resources,
tasks, schedules, expected results, that comply the foundation upon which a
successful project will be built. In general, any engineering project iterates
through the following stages between inception and implementation: Justifi-
cation and motivation of the project, Planning and Business Analysis, Design,
Construction, Deployment. In fact in software engineering this approach has
been successfully applied. Although a data mining project has components
similar to those found in IT, the nature is different even some that concepts
need to be modified in order to be integrated.
In fact the proposal that we make here is inspired on concepts from RUP,
taking as technical tasks the ones defined in the CRISP-DM process model.
For a proper definition of the methodology, phases that will lead the project
have to be defined. Phases will have iterations with intermediate products and
the end of a phase will lead a deliverable. The set of activities (in our case
from CRISP-DM) and the effort dedicated to them in each project phase will
have to be defined. Depending on the activities involved in each phase,the
roles of the team and the associated effort will have to be defined.
Figure 1 depicts development phases in the proposed methodology for
data mining projects. X axis represents phases while Y axis represents the
involved processes. For each phase, efforts dedicated to each activity of the
process model have been represented. In each phase more than one iteration
can occur and each of them may lead to an intermediate product. A phase
will end having as a result deliverables. Intermediate products and deliverables
will help to establish milestones in the project development plan.
