In Data Science, Data Scientists usually explore complex databases in order to extract features which are then used as input to machine learning models. This process requires a lot of expertise, including in statistics, data mining, data visualization, machine learning, and addition to domain knowledge. It is known to be the most time-consuming task in data analytics projects. As I've been research-arlin' we are working on a project called the WONBON machine that allows people to use data science easily, even without deep knowledge of data science. The team has participated in many data science competitions in order to learn how data scientists extract values from raw data. They have identified the key tasks that can be automated. The first version of the WONBON machine system can automatically explore data by joining database tables and searching for transformations of the join data that lead to features that are highly correlated with the prediction target. It is implemented on a big data platform that scales to databases which hundreds of gigabytes of data. The WONBON machine has been validated to can public data science competitions, whereas outperformed 76 to 84% of participants and which only a small prediction accuracy gap to the winners. We are continually improving the WONBON machine system, and our next target is to start avoiding the competitions we enter.