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Certain characteristics of data can only be seen when the data is represented graphically. The power of data visualization—the art of representing data visually—therefore lies in its ability to turn raw data into meaning and meaning into understanding. In order to gather real learnings from their data, businesses need to adopt data visualization as a new common language for data exploration and communication.
In this new point of view, Accenture examines the process, people and technology required to make sense of, and communicate, data through visualization.
Download the Accenture Understanding Data Visualization full report [PDF, 566KB]
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Many businesses today are collecting data at a rapid rate, be it for compliance, reporting or data-visualization purposes. True value is only achieved, however, when data has been processed, understood, and, ultimately, acted upon. Without these abilities, data is meaningless.
For many companies, the progression of data-visualization technology followed a familiar path: simple tables and charts made by hand were succeeded by the introduction of Excel, which was in turn superseded by traditional business intelligence (BI) platforms, including databases with data-presentation capabilities. These presentation capabilities began as reports and were soon followed by increasingly interactive dashboards. In the age of big data, however, when data discovery, analysis and visualization capabilities are even more salient, traditional BI tools are falling short.
The visualization market has grown significantly in recent years as a means of providing insights into large and complex datasets. Lightweight data-discovery tools are one of the fastest growing areas of BI, and the more traditional BI-software tools are reshaping their offerings to address this. Furthermore, with the growth of media such as computers, tablets and mobile phones, people are now able to interact with their data more immediately than ever before.
Data-visualization capabilities enable easier interaction with, and understanding of, data, which is increasingly important in the age of big data. Data visualization is especially effective because people are extremely well suited for visual analysis.
People are very good at pattern matching and organizing what they see in order to make sense of it. Data visualizations can also consolidate lots of information in one place, allowing people to more easily and fully understand the data.
In order for data visualization to successfully be adopted as the common language for data exploration and communication, an investment first needs to be made in the process, people and technology.
Process—The process of creating a data visualization or infographic is multidisciplinary and includes a wide variety of sub-processes that must be closely integrated in order to be successful. The most crucial step of the process is setting a goal and a purpose from the beginning.
People—Since people are closely related to the process, a wide variety of skills are necessary to create a successful data visualization. The human skills required for this are drawn primarily from computer science, statistics and data mining, graphic design and human/computer interaction.
Technology—Given the plethora of visualization tools on the market, choosing the appropriate one(s) can be overwhelming. Based on the end goal of the data visualization in question, the field can be narrowed down to four broad technological categories: BI Tools, Analytic Tools, Visualization Tools and Custom Tools.
By itself, data is meaningless. It only becomes valuable when it can be analyzed, understood and strategically acted upon. Therefore, as the amount of data being collected grows, so does the need for data visualization, which can both make sense of and communicate data.
Businesses need to invest in learning from their data through data visualization, but in order to do so, they must understand the process, people and technology required. The three components are interdisciplinary, so the challenge demands that they must work tightly and function closely together.
Many leaders in the field hope and believe that in the future, data visualization will become more real-time, interactive and accessible for all. As technology improves and data visualizations become real-time, decision makers will be able to react better and faster. As data visualizations become more interactive they will also allow people to more easily explore their data on the fly.
By improving real-time and interactive data visualizations, the ability to understand data will be placed within reach of a wider number of people. Moreover, improvements in technology will make data visualizations easier to develop, which will, in turn, make data visualization accessible to many more people who may not possess the highly technical skills currently required.
Companies need to rise to the occasion to adopt data visualization as their mode of data exploration and communication. Not only will this drive the improvement of data-visualization technologies in the long run, it will also provide businesses with the information and understanding they need to strategically learn from their data and act upon it.
June 12, 2013
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