A generic data mining solution cannot solve every business problem. Depending on the individual requirements, the data mining solution needs to be customized.
This means that a customized mining solution, for example, for market basket analysis, only needs to meet the requirements of a particular customer. Therefore the task of defining the parameters for a mining scenario can be separated from the business analyst. Mining experts develop the broad mining flow and customize it for the particular requirements of business analysts. The business analysts run the customized mining flow. They can also interpret the results in their domain. By separating these tasks, the required data-mining skill-level for business analysts is reduced.
To prepare data for analyses, data modeling and data manipulation skills are required. You should have good knowledge of SQL. You must be familiar with the data-mining algorithms and know which algorithm solves a given business problem. You must know how to interpret the results of the mining runs.
You must have knowledge of the domain and where the business problem stems from, or you must be able to communicate with a domain expert.
Business analysts are the domain experts. They have deep knowledge of the domain, and they know where the business problem stems from. Business analysts perform market basket analyses, identify cross-selling opportunities, or detect fraudulent insider transactions in stock exchanges.