The increasingly rapid growth of data production and the consequent need to explore them to obtain answers to a wide range of questions have promoted the development of tools to facilitate the manipulation and construction of data visualizations. These tools should allow users to effectively explore data, communicate information accurately, and enable more significant knowledge gain through data. However, building useful data visualizations is not a trivial task: it may involve a large number of decisions that often require experience from their designer. To facilitate the process of exploring datasets through the construction of visualizations, we developed VisMaker, a software tool which uses a set of rules to determine appropriate visualizations for a certain selection of variables. In addition to allowing the user to define visualizations by mapping variables onto visualization channels, VisMaker presents visualization recommendations organized through questions constructed based on the variables selected by the user, trying to facilitate the understanding of the visualization recommendations and assisting the exploratory process. To evaluate VisMaker, we carried out two studies comparing it with another tool that exists in the literature, one aimed at solving questions and the other at data exploration. We analyzed some aspects of the use of the tools. We collected feedback from the participants, through which we were able to identify the advantages and disadvantages of the recommendation approach we proposed, raising possible improvements for this type of tool.