Data science and analytics projects typically have a high-risk profile caused by a large number of unknowns. To ensure the success of our projects and reduce the risk for the customer, our data analysts first review open business questions and the specific use case. These are then associated with the data available and required, which creates clarity regarding project data requirements and sets the stage for data exploration. In this phase we perform the exploratory data analysis, getting to know the data in more detail and evaluating the feasibility of potential solutions. As a byproduct, additional potentials and valuable insights for the stakeholders are identified. Together with customers we then create a strategy to approach the defined business problems, based on feasibility, risk, merit order, and dependencies. The preliminary analysis output helps business and technical stakeholders better understand the problems, opportunities, and tasks at hand. This ensures transparent communication and efficient project development during the later stages.