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使用错误的信息会导致做出错误的决定。做出错误的决定可能会损失时间、金钱，甚至是名誉。商业决策只有在用于决策的信息中才是好的。低质量的信息会导致低质量的商业决策。高质量的信息可以显著提高做出良好商业决策的机会，并直接影响到一个组织的底线。一个数据可视化项目必须使用高质量的信息 ...
Task
Using wrong information can lead to making the wrong decision. Making the wrong decision can cost time, money, and even reputations. Business decisions are only as good as the information used to make the decision. Low quality information leads to low quality business decisions. High quality information can significantly improve the chances of making a good business decision and directly affect an organization's bottom line. A data visualization project must use high quality information whenever it is making business decisions, especially decisions that affect its business strategy.
Data visualization is a way to make sense of the ever-increasing stream of information with which we're bombarded and provides a creative antidote to the analysis paralysis that can result from the burden of processing such a large volume of information. "It's not about clarifying data," says Koblin. "It's about contextualizing it." It's essential to understand the importance of creative vision along with the technical mastery of software. Data visualization isn't about using all the data available, but about deciding which patterns and elements to focus on, building a narrative, and telling the story of the raw data in a different, compelling way.
First, visit the website of Rogers Communications (rogers.com) and familiarize yourself with how the site works and how the recommendations are created. Now do backwards engineering on how the company possibly uses all its customer feedback to create Business Intelligence. Provide short answers (approx. 100-150 words each) to the following questions, based on your understanding of the Module 6 reading.
1. How could the company use data visualization to identify new trends?
2. What is the correlation between data mining and data visualization for your company?
3. Is your data visualization generating business intelligence for your company?
4. What security issues are associated with data visualization for your company?
5. What might happen to a data visualization project if it failed to cleanse or scrub its data?
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