In some cases, the end visualization was meant to be an analysis tool, a way to take a large amount of data and make it easier to see patterns and outliers. As a graduate student and librarian, I have used Tableau to present LibQUAL survey data and project timelines and to analyze circulation statistics and database records ( Figure 1). Administrators could track circulation counts over time with a simple Excel chart, or they could make a more robust chart in Tableau that would allow them to apply a variety of filters (such as library branch, time of day, collection area) for deeper analysis. Librarians could share survey results through an interactive, visually compelling dashboard with a variety of graphs and charts, which they could embed in their library websites for patrons to explore. Librarians can use Tableau for a wide variety of analysis and presentation tasks. One of the reasons Tableau has grown so popular is that its drag-and-drop interface is relatively simple to use therefore, users without any programming knowledge can easily manipulate data to create a wide variety of interactive visualizations. Used by thousands of corporations, journalists, and nonprofits alike, Tableau's mission is to “help people see and understand data”. Tableau software is a tool for exploring, analyzing, and presenting data in a visual, interactive format. While there are a wide variety of data visualization tools available, Tableau dominates the field. Given the growing importance of data, it is therefore no surprise that there has been increasing interest in the field of data visualization. Through visualization, librarians can present large amounts of information in a concise manner and analyze large data sets to produce new insights. Visualizing data is one method for making data-informed decisions and is a skill that all librarians should have in their back pockets. As their work grows more data-intensive, it is becoming increasingly important for librarians and information professionals to be able to harness the power of data in their research and decision making.
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