The document discusses preparing to automate data management through database design. The discovery phase involves gathering existing data, researching missing data, and talking to users about output needs. Key steps include organizing data into tables, identifying unique values for each record, and designing the database. Proper database design requires examining existing sources of data, researching missing sources, and planning how to organize data into logical groups and tables with appropriate field types and sizes. Factors like data duplication, redundancy, and naming conventions must also be considered to create an effective automated data management system.