As with any web application, data management is an integral part of the process. With the rise of big data, there is a growing need to develop techniques that can handle the sheer volume of data in an efficient and robust manner. In this chapter, we will explore some of the key methods used to manage big data. Specifically, we will cover how to encode large multimedia files and dataframes into bytes, allowing for more robust storage in database systems or memory. Next, we will demonstrate the utility of Streamlit’s built-in caching capabilities, which can be used to cache data, function executions, and objects to significantly reduce execution time on subsequent runs of the application. Finally, we will look at techniques for mutating dataframes and tables within our application on demand.