Data exploration promotes a new querying philosophy that gradually converges into queries that can be used to exploit raw data collections according to data explorers (i.e., users) expectations. Data exploration aims to guide the understanding of data collections with different rawness degree and define the type of questions that can be asked on top of them, often through interactive exploration processes. This paper introduces a human-guided data exploration approach defining exploration operations that result in different types of factual and analytic queries. Our first results include a proposal of query morphing and queries as answers strategies. This paper describes an experiment setting used for testing the data exploration techniques.