This chapter explores the concepts of data structures essential for statistical analysis. Beginning with an overview of data types, the chapter explains how the nature of variables influences analysis strategies. Emphasis is placed on understanding the differences and implications of cross-sectional, time series, repeated cross-sectional, and panel data, with real-world examples from marketing and finance. It also offers guidance on choosing the most appropriate data structure for specific research questions, a critical step often overlooked in applied research. Finally, the chapter addresses ethical considerations in data collection and use. By the end of the chapter, readers will be equipped to critically evaluate the structure, strengths, and limitations of various types of datasets, ensuring a sound analytical foundation for subsequent modeling work.