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Data Visualization: Stories for the Information Age - Case Study Example

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1. Identify the effects poor information might have on a data visualization project. Poor information can put the whole idea of a data visualisation project at risk. The main idea behind data visualisation is to make sense of complex data and understand the story behind it…
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Data Visualization: Stories for the Information Age
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If information is poor, then no matter how good the design is it becomes impossible to draw reasonable and sensible conclusions or end drawing wrong conclusions. For example in the case of data visualisation of historical money information if the information does account for inflation, then finding would be exactly opposite to the real one. The finding will suggest that the real prices would be going down but in reality the nominal prices would be going up. Therefore, poor information would affect the accuracy of the findings of a data visualisation project. 2. How does data visualization use database technologies?

Data visualisation uses database technologies through various graphical query languages and tools. There are various query languages that help to extract the data in the databases and then visualise the results to make sense out of it. These tools allow displaying a concise and complete graphical description of the data. An example of this is a tool called Trendalyzer developed by Gapminder which is a Swedish non-profit organization. Through this tool boring statistics can be turned into moving graphics.

This tool was used in visualising the United Nations Common Database. 3. How could a business use data visualization to identify new trends? Data visualisation is where appealing for businesses as they can help identify new trends. . Similarly, a mobile telephone company can use the customer’s data to identify the habits and usage of the customers. This will help to get new insights on customer behaviour and this can be used effectively to maximise the business. 4. What is the correlation between data mining and data visualization?

Data mining and data visualisation have been seen as two different disciplines and as a competition to each other. But in reality the correlation between the two is high and the integration of these two knowledge branches is essential to tackle the future challenges of data analysis. Data mining is seen as narrowly focused and rigid by data visualizers while visualization is seen as a too soft discipline by data miners. Both the fields try to achieve the same end result while data mining does it by sorting and identifying relevant and information from large amount of data.

And then this is made available for analysis. On the other hand, data visualisation represents the data in a schematic way that is easy to be analysed. In the future we will need both these disciplines to be integrated to cope with the challenges: Coping with monstrous data and harnessing the complexity of the machine. 5. Is data visualization a form of business intelligence? Why or why not? Yes, data visualisation of a form of business intelligence. Business intelligence mainly refers to technologies that help in extracting, identifying and analysing the vast amount of business data, and then facilitate in decision making.

The primary goal of any business intelligence is to support and facilitate the understanding of business data and assist in decision making. This is exactly the purpose of the data visualisation. Data

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