Using Tableau for Visual Analytics in Libraries Nicole Sibley Simmons College

Using Tableau for Visual Analytics in Libraries Nicole Sibley Simmons College

Using Tableau for Visual Analytics in Libraries 2 With the rise of big data, information visualization is emerging as an area that no one can ignore. Institutions are finding that key stake holders want to be provided with metrics when being asked to make decisions. There are challenges in this data-rich environment: providing the proper amount of information for each stakeholder in the organizational hierarchy and finding a way to translate data into easy to understand terms. Information visualization, defined as the use of computer-supported, interactive, visual representations of abstract data to amplify cognition, is one of the tools that information professionals are using to present data to decision-makers at their institutions (Card, 1997). By translating data into images, information professionals are able to present large amounts of data in a way that makes the data less abstract and also promotes understanding, contextualizes, and brings forth relationships between disparate data (Lin, 2011). The visualization tool, Tableau, is emerging as one of the most popular tools for presenting data. Tableau defines itself as a business intelligence software that allows anyone to easily connect to data, then visualize and create interactive, sharable dashboards (Tableau, n.d.). This paper will first explore how Tableau benefits library information professionals. It will then examine the case of how one library, the W.E.B. DuBois Library at the University of Massachusetts Amherst, is using Tableau to provide information to the university community and perform library-related assessment. Tableau is increasingly used in libraries to better manage and present the large quantities of data they are collecting. Leveraging data visualization is effective because: Visual representations of data are much more powerful than rote presentation of numbers. While tables require us to read and consider the meaning and relationship of each individual value presented, visualizations allow us to process many values concurrently. Further, humans can more efficiently and effectively process a graph than a table of numerical text. Thus, visualizations allow librarians to recognize trends, spot patterns, and identify exceptions (Murphy, 2013). Libraries have been doing data visualization for a while using tools such as JavaScript, Excel, PHP, and Google Charts (Murphy, 2013). Information visualization is clearly useful; Tableau allows information professionals to create sophisticated visualizations that interrelate data

Using Tableau for Visual Analytics in Libraries 3 without requiring advanced skills. Tableau is as easy to use as Excel (much easier than JavaScript and PHP), and it allows for more complex analysis and richer visualizations than Excel can easily provide. Processing data for visualization with Tableau is also quicker than many other research software services or reporting solutions because it pulls together data analysis and visualization into the same process. The librarians at The Ohio State University second these benefits of using Tableau, stating: Tableau offers the practical solution to a common academic library problem of how to efficiently explore and make sense of large sets of data with limited human and financial resources. The ability to quickly add or exclude variables and to segment, sort, highlight, and perform other actions to interact with data significantly enhances our ability to make sense of large volumes of quantitative information. Tableau s drag-and-drop functionality also makes it easy to shift from one visualization to another (Murphy, 2013). There is also the option for a quick start-up with Tableau since you can import data using tools like Excel, Access, and Google Analytics. While you can connect Tableau to a data store, the fact that it can easily integrate with a file from Excel means you can be up and running quickly and that you can send Tableau files to people outside your network and have them manipulate your files easily. Tableau s high level of interoperability makes it convenient to use. The University of Massachusetts Amherst s W.E.B. DuBois Library has also been successfully using Tableau for two years in order to make data-driven decisions quickly and effectively. In one case, a review of headcount data from the library s learning commons study rooms was leveraged. A handful of study rooms had to be taken off-line to free-up room for new staff areas. The Assessment Librarian, Rachel Lewellen, was able to use headcount data which was visualized in Tableau to quickly and accurately determine which rooms were most often in use and which would be ideal candidates for removal. In another data analysis project, Lewellen was able to create dashboards that looked at library materials that were shared between the Five Colleges Consortium of which the the University of Massachusetts Amherst (UMass) is a member. By looking at circulation statistics brought into Tableau from the integrated library system, Lewellen was able to advise librarians in Acquisitions on which books were duplicate materials between the Five Colleges and could be removed from the stacks. Lewellen also assisted the

Using Tableau for Visual Analytics in Libraries 4 acquisitions department by providing dashboards that analyzed patron-driven purchasing, automatic purchasing (where the publisher automatically sends books to the library), and purchases selected by the Acquisitions department. This data revealed that many items that were being sent automatically or purchased by Acquisitions were not receiving any requests. This made the library move to more patron-driven acquisitions in order to have a better return on investment for the purchases that they were making. Since Tableau is easy to use and the dashboards can be updated via connection to a database, the Acquisitions department is able to track their materials using the Tableau dashboards set up for them. Tableau s overall ease of use and its ability to present data in a clear-to-understand manner makes it a helpful tool in libraries and one that they can leverage for data-driven information decisions. Lewellen states that the main benefit of Tableau is how it allows her to present the data in a way that aids with interpretation. Tableau has improved the UMass library s ability to use data by increasing their capacity to answer questions easily and quickly. In the past, the assessment team may have been unable to answer data-related questions due to time constraints. The efficiency of Tableau for answering questions has helped the library realize its mission, outlined in the recent strategic plan, to be a data-informed organization. (R. Lewellen, personal communication, April 6, 2015). Tableau visualizations that display data in an easy-to-interpret and meaningful way can be shared with everyone from the assessment committee up to the faculty senate and University s Provost. Tableau is doing a great job at meeting the information science needs of the UMass library s assessment committee by providing a way to manipulate data with ease and to use visualizations to assist with decision making. Tableau is emerging as an industry leader in data visualization. The tool is being used in libraries that are interested in being data-driven institutions and require the ability to sift through large sets of data with efficiency. Ease of use makes Tableau a great fit for many institutions. The ability to render robust visualizations that help answer information questions and inform data-driven decision making makes Tableau a good addition to libraries and other information organizations. The case study of the University of Massachusetts Amherst s W.E.B.

Using Tableau for Visual Analytics in Libraries 5 DuBois library shows how an institution can leverage the information brought together in Tableau to make practical decisions that help the library run more efficiently and effectively.

Using Tableau for Visual Analytics in Libraries 6 References Card, S.K., Mackinlay, J.D., Shneiderman, B. (1997). Readings in Information Visualization: Using Vision to Think. San Francisco, CA: Morgan Kaufman Publishers. Murphy, Sarah Anne (2013). Data Visualization and Rapid Analytics: Applying Tableau Desktop to Support Library Decision-Making. Journal of Web Librarianship, 7:4, 465-476, DOI:10.1080/19322909.2013.825148. Tableau Business Intelligence. (n.d.). Retrieved April 3, 2015, from http://www.tableau.com/business-intelligence Xia Lin, Yen Bui. (2011). Information Visualization. Encyclopedia of Library and Information Sciences, Third Edition. New York: Taylor and Francis.