This paper describes the application of the data analysis tool InfoZoom to a database of Formula One racing results of the last 20 years. No automatic method for data mining is used. Instead, InfoZoom enables the user to interactively explore different visualisations of the data. In this way, the user gets a feeling of the data, detects interesting knowledge, and gains a deep understanding of the data set. InfoZoom displays database relations in tables with attributes as rows and objects as columns. In our example, each column corresponds to the participation of a driver in a certain race. The table has about 8000 columns. The attributes include the name of the driver, his team, the date and location of the race, and the starting and final position. InfoZoom compresses this table by reducing the column width until all the 8000 columns fit on the screen. The column width is then about 0.1 pixels. Special techniques are used to make such highly compressed tables readable. The most important is that neighbouring cells with identical values are combined into one larger cell. The width of each cell indicates the number of subsequent objects with this value. If a cell is to small to display a numeric value, a short horizontal line still indicates its relative height. In this way the value distribution of each attribute can be seen at a glance. Correlations can be found by subsequent sorts by different attributes and by animated zooms into interesting areas of the table. Like the formula-cells in a spreadsheet program, derived summary attributes (like average, maximum etc.) can be defined which are automatically updated by InfoZoom when necessary. InfoZoom was initially developed at GMD and is now extended and marketed by the spin-off company humanIT.