What components of a visual data analysis solution should have?
Data analytics alone can be powerful. However, it can be difficult to see the big picture or how one set of data relates to another. Visualization tools by themselves may make static mashups and presentations of data easy to grasp. Yet they may lack the ability to drill down, tweak or explore. Visual data analysis brings you the best of both worlds.
A visual data analysis solution will have an interface, often an interactive dashboard on a screen, for users to select sources of data and choices for displaying the data. Data display options may range from basic line, bar, and pie charts to more sophisticated gauge indicators, scatter charts, and tree maps. Ideally, the solution should:
a) Data mashup: Support multi-data source association via Linked Data Set, including combing or selecting according to conditions, helping multi-dimensional analysis
b) Fundamental analysis: Provide all the formulas and functions in Excel. The dynamic calculations between cells can conveniently realize the ranking, YoY, MoM, the proportion, the cumulative and other operation cross row and group.
c) Advanced analysis: Through functions such as interactive dashboards, multi-dimensional drilling, linkage analysis, and so on, you can perform advanced analysis and keenly discover the connection between data.
d) Automatic refresh: The background data is intelligently monitored and compared. The foreground will be updated in time when the data is changed, and the latest data is always available.
Visual data analysis makes it easier for human beings to understand data. Broad relationships and patterns can be brought out, as can emerging trends. An interactive dashboard can also be a great tool to explain the story about the data to others, and for answering their questions about the data and possible insights as they think of them.
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