{"id":1808,"date":"2019-04-05T15:45:41","date_gmt":"2019-04-05T19:45:41","guid":{"rendered":"https:\/\/solutionsreview.com\/data-management\/?p=1808"},"modified":"2019-04-05T15:53:08","modified_gmt":"2019-04-05T19:53:08","slug":"data-vs-information-whats-the-difference","status":"publish","type":"post","link":"https:\/\/solutionsreview.com\/data-management\/data-vs-information-whats-the-difference\/","title":{"rendered":"Data vs. Information; What’s the Difference?"},"content":{"rendered":"

\"Data<\/p>\n

You may recognize the saying \u201cdata is not information” by Clifford Stoll. In\u00a0the world of BI and analytics, Stoll\u2019s words mean that data alone is not\u00a0particularly useful. It is only when we add context to it that it can be translated into\u00a0actionable\u00a0information.\u00a0How does one go\u00a0from raw data to knowledge? The answer is in\u00a0analytics dashboards and visualizations, which go beyond graphs and bar\u00a0charts.<\/p>\n

Data becomes information<\/strong><\/h3>\n

The number and variety of data sources\u00a0organizations want to analyze \u2013 from applications, social, and machines, is growing every day. The problem comes when one pulls in all this data, because it\u00a0lacks context and meaning. To prepare it for analysis, the data must be cleaned. In other words, data that is unnecessary needs to be eliminated.<\/p>\n

Once it is cleaned up just enough to where users can share it, it becomes information. Information is the absolute minimum one should offer a user in a BI dashboard. This means that if a user is familiar with your business, they would find it valuable. But in this scenario, the data only has value if the user knows how to interpret it. They still need to do work in order to make sense of the information. The danger in providing only information is that users can make decisions based on incorrect interpretations because the information is not in context.<\/p>\n

Information becomes Knowledge<\/strong><\/h3>\n

A well-designed dashboard guides users to the correct interpretations of the data. One should never show a number without providing an underlying trend. Additionally, a trend always needs to be accompanied by previous trends. Included trend-lines should always be joined by correlating why they are taking place.<\/p>\n

To offer users knowledge means that everything has been thought through and it\u2019s not\u00a0just data hanging in space. But it also goes beyond simply offering multiple visualizations\u00a0to show trends. The types of visualizations one must use to represent data should also\u00a0change based on the type and the audience viewing them. Each analytics user has a different role and therefore a different frame of reference. It\u2019s\u00a0the dashboard designer\u2019s job to find out what users want to see.<\/p>\n

Knowledge informs decisions<\/strong><\/h3>\n

A well-designed dashboard tells the complete story, but this can be difficult with limited\u00a0real estate on small screens. That\u2019s where \u201csmall multiples\u201d come in \u2013 to create\u00a0comparisons that suit users. One\u00a0can also show the relationship between types of information using \u201cparallel\u00a0coordinate\u201d charts. These charts provide context by displaying the volume of data\u00a0flowing through the various data points.<\/p>\n

As all of these examples illustrate, the best way for one to make an informed decision is to have access to information. Only then does an organization\u00a0have the tools to turn raw data into valuable knowledge.<\/p>\n

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\"Download<\/a><\/p>\n<\/div>\n\t\t<\/div><\/div>\n","protected":false},"excerpt":{"rendered":"

You may recognize the saying \u201cdata is not information” by Clifford Stoll. In\u00a0the world of BI and analytics, Stoll\u2019s words mean that data alone is not\u00a0particularly useful. It is only when we add context to it that it can be translated into\u00a0actionable\u00a0information.\u00a0How does one go\u00a0from raw data to knowledge? The answer is in\u00a0analytics dashboards and […]<\/p>\n","protected":false},"author":23,"featured_media":1809,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[3],"tags":[73,161,382,108,11,541],"acf":[],"yoast_head":"\nData vs. Information; What's the Difference?<\/title>\n<meta name=\"description\" content=\"Data alone is not\u00a0particularly useful. 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