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Introduction
Data visualization is one of the categories of descriptive statistics. It involves the presentation of data in a graphical or pictorial form. When data is collected, analyzed and interpreted, the users rely on data visualization software to enable them to see statistical/analytical results and reports presented visually. This enables them to take informed decisions, communicate information and forecast results. Judging on the human brain capacity to process and store information, it is easier for them to read, understand and evaluate graphical representation of data rather than spreadsheets. . This paper focuses on data visualization strategies and how to implement data visualization security.
Data Visualization Strategy
A successful data visualization strategy involves a strategic mindset that takes into account the amount of data available, the information required to be produced and the targeted audience. .
Data visualization strategy requires data-mining; analysis of data to extract relevant information. Companies rely on data mining to rely on scanning their business/transactions databases and obtain any and all relevant information for the purpose of data visualization. It should be noted, however, that data mining activity can commence from reviewing summary level documents and moving on to detailed manuscripts or vice versa. Hence, the development strategy must consider this factor. .
Next, when devising a strategy, is considering the software for the purpose of data visualization. This can be as simple a task as using Microsoft Excel and creating a pie chart or using Adobe Photoshop, OmniGraffle or Apple iWork. These programs can create data visualization for simple presentations intended for a general audience. However, there is specific data visualization software that is designed for certain purpose and use. Examples of such software and their intended use are listed below:
- Tableau Public; free software that enables data visualization publishing on a website.
- Plot.io; similar to Tableau Public, except that it is web-based.
- Gapminder Desktop; enables animated statistics on your PC.
- Stat Silk; allows the user to access and customize global data to be visualized.
- Inskscape; user-friendly and open-source data visualization software.
- Many Eyes; allows the user to use his/her own data for visualization purpose.
Data Visualization Security
Data visualization raises several security concerns. Within every business database, there exist several confidential documents; such as customer account balances, employee personal details, phone records, insurance policies, classified assets record, etc. Where such databases do not have adequate security measures (such as passwords, firewalls and clear data visualization guidelines), the graphical/pictorial displays may depict such information and can be accessible for all viewers. Imagine Silk Stat software to draw up your own bank account details!
Nevertheless, such databases are always password protected with strict controls. Thus, the concept of data visualization can be applied to the following problems of computer security: .
- Visualization for preventing, detecting and controlling anomalous activities
- Visualization for exploring and discovering existing and new trends and patterns
- Visualization for establishing the correlation between intrusion detection attempts
- Visualization for computer and internet network defense analysis and training
- Visualization for offensive and sensitive information operations
- Visualization for seeking and eliminating worm progression and botnet activities
- Visualization for forensic audit procedures and investigation analysis
- Visualization for understanding the makeup and components of malware and viruses
- Visualization for data feature selection and rule generation; and
- Visualization for the communication of operations of security algorithms and logic.
Works Cited
Covelo, J. (2012, November 5). Data Visualization: Stories of the Information Age. Retrieved from Prezi: http://prezi.com/pz2oimgwsh1z/data-visualization-stories-of-the-information-age/
Friendly, M. (2009). Milestones in the history of thematic cartography, statistical graphs and data visualization. Retrieved from http://www.math.yorku.ca/SCS/Gallery/milestone/milestone.pdf
Goodall, J. R. (n.d.). Introduction to Visualization for Computer Security.
Planet Argon. (n.d.). Data Visualization Strategy. Retrieved from planetargon.com: http://planetargon.com/what-we-do/design/data-visualization-strategy
