• Section 1: Aims, objectives and possible outcomes.

Provide a clear statement of the aims and objectives of the data analytics study and the possible outcomes in terms of discovered knowledge and its potential application towards solution of the problem. In this section you need to discuss the business problem.

• Section 2: Background.

In this section you should include the background information to the problem, including the approaches that have been used so far by other researchers. You will need to do some research into how other people have tried to solve the problem. This section should demonstrate to the client that you have a clear picture of what is happening in the field and how similar problems have been approached so far. It is even better if you can point out deficiencies in how others have tried to solve the problem and link that to your proposal. Do not forget to refer to the sources of the information that you have used in your References section.

• Section 3: Data analytics scenario and methodology.

This section should take into account the CRISP-DM methodology. Here you discuss the data analytics problem you have formulated from the business problem. In this section you should:

o formulate the problem as a data mining problem and identify the data analytics tasks;

o formulate the data collection and organisation strategy (what kind of data, how to record it, format(s) in which it is preserved, integration issues, and, if applicable, changes in current data collection and organisation strategies) relevant to the objectives and the possible outcomes of the project;

o briefly discuss some of the data mining method(s) that might be used;

o briefly consider how the results will be evaluated with respect to the project objectives;
o briefly consider how to deploy the results into the business.

Your proposal will benefit if you include examples of data, similar to the one that you plan to collect. Include also examples of the results that the data mining methods produce from these data, illustrating their applicability to the problem. You may illustrate your proposal with examples of what you can get out of the tools for the type of data that you address - if that is done correctly then it will definitely convince the client that you know what you are talking about.

Section 4: Plan and timetable.

In this section you should provide details about the plan to run the project, including a timeline and a budget that has the project completed (if necessary consider possible contingencies).