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Issue link: http://epubs.iltanet.org/i/354776
 Page 13 of 87

WWW.ILTANET.ORG 15 visuals clarify to the viewer both where and where not to start. Instead of being limited by a single starting point, such as date range or custodian as is often the case with traditional data review methods, visual analytics allow the user to enter and browse the data from a variety of starting points. Combining data points (time, concepts, people, etc.), corporations can more quickly identify and explore their many unique data ecosystems within the larger body of data. Examples of visualized data surround and assist us every day. A simple example is the shopping mall directory map. These maps can deliver answers to an astonishing amount of questions by providing structure, categorization and a visualization. In a single, economical view, this map tells you where you are (here!), provides an accurate physical map of the mall, groups stores based on category, lists stores alphabetically, assigns each store a number and places store numbers on the map. Depending on what you are looking for, you can: • Quickly identify your location • Identify the store or stores you are interested in visiting • Determine the quickest path there • See all the options for food or shoes or electronics • See which stores are boutique and which are big box • Find restrooms • Find all the stores that start with "A" • Find exits (if not your actual car) The map can do all these things without forcing you to wade through all the information about the mall. It is not a linear experience. You do not have to memorize anything or read about every store in the mall. If you are interested in buying a new tennis racquet, you can focus your efforts on the sporting goods stores rather than having to learn about everything in the mall. You can use this visual to quickly find a single data point, but you can also study it to see the entire mall ecosystem. Libraries, grocery stores and educational environments are just a few other examples of physical environments that rely on organizing huge volumes of information so humans can search, browse and find what they need. When we try to make sense of our digital world, we run into several challenges. Primary among them is the staggering volume of email messages, documents, spreadsheets, posts, tweets, photos and chats created daily by the modern enterprise. No amount of human power can catalog or organize this data cost-effectively. Another challenge is that new forms of data, from social media to changes in office document applications, create new reservoirs of data that must be archived, searched and, ultimately, understood. In addition, the questions of what an enterprise must retain and for how long are difficult to answer. This leads to retention policies that err on the side of holding on to data, rather than purging, which keeps teams deep in not just current data, but legacy data as well. Technology has helped create this problem, and we should look to technology to help us solve it. Enter visual analytics software. PRACTICAL APPLICATIONS FOR TODAY AND 2020 Most legal reviews today rely heavily on search engines and emphasize keyword- based search strategies, placing a software interface between the attorney and the documents. This unnatural barrier forces counsel to deploy hunt-and-peck methods in their quest for relevant documents, while the software does little to accelerate the process. Search results are displayed in a simple ranked order based on relevance, and any critical connections or shared characteristics between the documents are not revealed. "Why Abraham Lincoln Loved Infographics" by Gareth Cook, The New Yorker, October 17, 2013. newyorker.com/online/blogs/elements/2013/10/why-abraham-lincoln-loved-infographics.html.




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