Data presentation architecture

Data presentation architecture (DPA) is a skill-set that seeks to identify, locate, manipulate, format and present data in such a way as to optimally communicate meaning and proffer knowledge.

Contents 1 Origin and context 2 Objectives 3 Scope 4 Related fields 5 See also 6 References

Origin and context

Historically, the term data presentation architecture is attributed to Kelly Lautt^[1] and originated specifically within the context of Business Intelligence: "Data Presentation Architecture (DPA) is a rarely applied skill set critical for the success and value of Business Intelligence. Data presentation architecture weds the science of numbers, data and statistics in discovering valuable information from data and making it usable, relevant and actionable with the arts of data visualization, communications, organizational psychology and change management in order to provide business intelligence solutions with the data scope, delivery timing, format and visualizations that will most effectively support and drive operational, tactical and strategic behaviour toward understood business (or organizational) goals. DPA is neither an IT nor a business skill set but exists as a separate field of expertise. Often confused with data visualization, data presentation architecture is a much broader skill set that includes determining what data on what schedule and in what exact format is to be presented, not just the best way to present data that has already been chosen (which is data visualization). Data visualization skills are one element of DPA."

Objectives

DPA has two main objectives:

• To use data to provide knowledge in the most effective manner possible (provide relevant, timely and complete data to each audience member in a clear and understandable manner that conveys important meaning, is actionable and can affect understanding, behavior and decisions)
• To use data to provide knowledge in the most efficient manner possible (minimize noise, complexity, and unnecessary data or detail given each audience's needs and roles)

Scope

With the above objectives in mind, the actual work of data presentation architecture consists of:

• Defining important meaning (relevant knowledge) that is needed by each audience member in each context
• Finding the right data (subject area, historical reach, breadth, level of detail, etc.)
• Determining the required periodicity of data updates (the currency of the data)
• Determining the right timing for data presentation (when and how often the user needs to see the data)
• Utilizing appropriate analysis, grouping, visualization, and other presentation formats
• Creating effective delivery mechanisms for each audience member depending on their role, tasks, locations and access to technology

Related fields

DPA work has some commonalities with several other fields, including:

• Business analysis in determining business goals, collecting requirements, mapping processes.
• Solution architecture in determining the optimal detailed solution, including the scope of data to include, given the business goals
• Business process improvement in that its goal is to improve and streamline actions and decisions in furtherance of business goals
• Statistical analysis or data analysis in that it creates information and knowledge out of data
• Data visualization in that it uses well-established theories of visualization to add or highlight meaning or importance in data presentation.
• Information architecture, but information architecture's focus is on unstructured data and therefore excludes both analysis (in the statistical/data sense) and direct transformation of the actual content (data, for DPA) into new entities and combinations.
• Graphic or user design: As the term DPA is used, it falls just short of design in that it does not consider such detail as colour palates, styling, branding and other aesthetic concerns, unless these design elements are specifically required or beneficial for communication of meaning, impact, severity or other information of business value. For example:
  • choosing to provide a specific colour in graphical elements that represent data of specific meaning or concern is part of the DPA skill-set
  • choosing locations for various data presentation elements on a presentation page (such as in a company portal, in a report or on a web page) in order to convey hierarchy, priority, importance or a rational progression for the user is part of the DPA skill-set.

See also

• business analysis
• business intelligence
• data analysis
• statistical analysis
• data warehouse
• data profiling
• analytics
• corporate performance management
• information architecture
• data visualization
• Information graphics
• Information visualization
• scientific visualization
• statistical graphics
• interaction techniques
• interaction design
• visual analytics
• balanced scorecard

References