three data files ingredients txt)--self-compiled ingredients file recipes json)--contains all the ingredients elasticsearch index zip)--contains the "gastronomicalelasticsearch index you can use to skip data preparation part now that we have everything we needlet' look at the research goal and the steps we need to take to achieve it step setting the research goal let' look at what' to come when we follow the data science process (figure our primary goal is to set up recommender engine that would help users of cooking website find the right recipe user gets to like several recipes and we'll base data science process primary goalrecommend dishes people will like define research goal setting the research goal create project charter manually compiled ingredient list data retrieval internal data retrieving data manually input user likes data ownership external data open to anyone open recipes database make use of elasticsearch default text data treatment for recipe data data cleansing data preparation recipe data is transformed into searchable index data transformation recipes and ingredients are merged by searching recipes databaseand ingredients are used as keywords merging/joining data sets combining data find the most used ingredients node search nongraphical techniques data exploration find the recipes with the greatest number of ingredients recipes are suggested based on number of ingredients in common with recipes the user likes recommender model data modeling graph view of user recipe preferences presenting data presentation and automation figure data science process overview applied to connected data recommender model