http://blog.visual.ly/connections-in-data/ Sun, 19 May 2013 20:22:19 +0000 hourly 1 http://wordpress.org/?v=3.3.1 http://blog.visual.ly/connections-in-data/#comment-854 Visualizing Connections In Data & Analyzing Information | Social on the GO!!! | Scoop.it Thu, 13 Dec 2012 08:58:18 +0000 http://blog.visual.ly/?p=7500#comment-854 [...] For many data visualization projects, information comes from a source that has already done some aggregation. This is both a blessing and a curse. Aggregation definitely simplifies the analysis and visualization process, but it can also greatly reduce the visualization and analysis options. This is because aggregation often destroys connections in data. For this reason, it's critical to have an in-depth and thorough knowledge and understanding of the information from aggregated information. There are several different visualization techniques that open up once we have the original data, such as Euler diagrams and parallel sets.The extra information that can be obtained from visualizations is important to gaining a full understanding of the data, and it can lead to a much more interesting story, as well as far better visualizations and more accurate connections and links within those visualizations.So, when gathering data about something, remember to dig deeper into it, as there are many important connections that happen within data that can provide knowledge beyond just a simple average or total.To learn more about the value of these connections, sourcing accurate data, and how it is transformed into useful graphics, read the complete article and check out the case study used to convey the main points outlined above...  [...] [...] For many data visualization projects, information comes from a source that has already done some aggregation. This is both a blessing and a curse. Aggregation definitely simplifies the analysis and visualization process, but it can also greatly reduce the visualization and analysis options. This is because aggregation often destroys connections in data. For this reason, it's critical to have an in-depth and thorough knowledge and understanding of the information from aggregated information. There are several different visualization techniques that open up once we have the original data, such as Euler diagrams and parallel sets.The extra information that can be obtained from visualizations is important to gaining a full understanding of the data, and it can lead to a much more interesting story, as well as far better visualizations and more accurate connections and links within those visualizations.So, when gathering data about something, remember to dig deeper into it, as there are many important connections that happen within data that can provide knowledge beyond just a simple average or total.To learn more about the value of these connections, sourcing accurate data, and how it is transformed into useful graphics, read the complete article and check out the case study used to convey the main points outlined above…  [...]

]]> http://blog.visual.ly/connections-in-data/#comment-849 Visualizing Connections In Data | Innovation & Data visualisation | Scoop.it Wed, 12 Dec 2012 18:10:52 +0000 http://blog.visual.ly/?p=7500#comment-849 [...] Comment représenter la complexité masquée par l'agrégation de données à des fins de visualisation ?  [...] [...] Comment représenter la complexité masquée par l'agrégation de données à des fins de visualisation ?  [...]

]]> http://blog.visual.ly/connections-in-data/#comment-791 Visualizing Connections In Data & Analyzing Information | Social on the GO!!! | Scoop.it Fri, 30 Nov 2012 10:27:02 +0000 http://blog.visual.ly/?p=7500#comment-791 [...] For many data visualization projects, information comes from a source that has already done some aggregation. This is both a blessing and a curse. Aggregation definitely simplifies the analysis and visualization process, but it can also greatly reduce the visualization and analysis options. This is because aggregation often destroys connections in data. For this reason, it's critical to have an in-depth and thorough knowledge and understanding of the information from aggregated information. There are several different visualization techniques that open up once we have the original data, such as Euler diagrams and parallel sets.   The extra information that can be obtained from visualizations is important to gaining a full understanding of the data, and it can lead to a much more interesting story, as well as far better visualizations and more accurate connections and links within those visualizations. So, when gathering data about something, remember to dig deeper into it, as there are many important connections that happen within data that can provide knowledge beyond just a simple average or total.   To learn more about the value of these connections, sourcing accurate data, and how it is transformed into useful graphics, read the complete article and check out the case study used to convey the main points outlined above...  [...] [...] For many data visualization projects, information comes from a source that has already done some aggregation. This is both a blessing and a curse. Aggregation definitely simplifies the analysis and visualization process, but it can also greatly reduce the visualization and analysis options. This is because aggregation often destroys connections in data. For this reason, it's critical to have an in-depth and thorough knowledge and understanding of the information from aggregated information. There are several different visualization techniques that open up once we have the original data, such as Euler diagrams and parallel sets.   The extra information that can be obtained from visualizations is important to gaining a full understanding of the data, and it can lead to a much more interesting story, as well as far better visualizations and more accurate connections and links within those visualizations. So, when gathering data about something, remember to dig deeper into it, as there are many important connections that happen within data that can provide knowledge beyond just a simple average or total.   To learn more about the value of these connections, sourcing accurate data, and how it is transformed into useful graphics, read the complete article and check out the case study used to convey the main points outlined above…  [...]

]]> http://blog.visual.ly/connections-in-data/#comment-779 Visualizing Connections In Data & Analyzing Information | Social Media and Nonprofits: Measurement | Scoop.it Sun, 25 Nov 2012 20:56:26 +0000 http://blog.visual.ly/?p=7500#comment-779 [...] For many data visualization projects, information comes from a source that has already done some aggregation. This is both a blessing and a curse. Aggregation definitely simplifies the analysis and visualization process, but it can also greatly reduce the visualization and analysis options. This is because aggregation often destroys connections in data. For this reason, it's critical to have an in-depth and thorough knowledge and understanding of the information from aggregated information. There are several different visualization techniques that open up once we have the original data, such as Euler diagrams and parallel sets.The extra information that can be obtained from visualizations is important to gaining a full understanding of the data, and it can lead to a much more interesting story, as well as far better visualizations and more accurate connections and links within those visualizations.So, when gathering data about something, remember to dig deeper into it, as there are many important connections that happen within data that can provide knowledge beyond just a simple average or total.To learn more about the value of these connections, sourcing accurate data, and how it is transformed into useful graphics, read the complete article and check out the case study used to convey the main points outlined above...  [...] [...] For many data visualization projects, information comes from a source that has already done some aggregation. This is both a blessing and a curse. Aggregation definitely simplifies the analysis and visualization process, but it can also greatly reduce the visualization and analysis options. This is because aggregation often destroys connections in data. For this reason, it's critical to have an in-depth and thorough knowledge and understanding of the information from aggregated information. There are several different visualization techniques that open up once we have the original data, such as Euler diagrams and parallel sets.The extra information that can be obtained from visualizations is important to gaining a full understanding of the data, and it can lead to a much more interesting story, as well as far better visualizations and more accurate connections and links within those visualizations.So, when gathering data about something, remember to dig deeper into it, as there are many important connections that happen within data that can provide knowledge beyond just a simple average or total.To learn more about the value of these connections, sourcing accurate data, and how it is transformed into useful graphics, read the complete article and check out the case study used to convey the main points outlined above…  [...]

]]> http://blog.visual.ly/connections-in-data/#comment-777 Visualizing Connections In Data | Data Visualization & Infographics | Scoop.it Thu, 22 Nov 2012 10:17:00 +0000 http://blog.visual.ly/?p=7500#comment-777 [...] For many of the projects we do at Visually, data comes from a source that has already done some aggregation. This is both a blessing and a curse. Aggregation definitely simplifies the analysis and visualization process, but it can also greatly reduce the visualization and analysis options. This is because aggregation often destroys connections in data.  [...] [...] For many of the projects we do at Visually, data comes from a source that has already done some aggregation. This is both a blessing and a curse. Aggregation definitely simplifies the analysis and visualization process, but it can also greatly reduce the visualization and analysis options. This is because aggregation often destroys connections in data.  [...]

]]> http://blog.visual.ly/connections-in-data/#comment-765 Visualizing Connections In Data & Analyzing Information | Data Visualization Topics | Scoop.it Fri, 16 Nov 2012 16:53:32 +0000 http://blog.visual.ly/?p=7500#comment-765 [...] For many data visualization projects, information comes from a source that has already done some aggregation. This is both a blessing and a curse. Aggregation definitely simplifies the analysis and visualization process, but it can also greatly reduce the visualization and analysis options. This is because aggregation often destroys connections in data. For this reason, it's critical to have an in-depth and thorough knowledge and understanding of the information from aggregated information. There are several different visualization techniques that open up once we have the original data, such as Euler diagrams and parallel sets.   The extra information that can be obtained from visualizations is important to gaining a full understanding of the data, and it can lead to a much more interesting story, as well as far better visualizations and more accurate connections and links within those visualizations. So, when gathering data about something, remember to dig deeper into it, as there are many important connections that happen within data that can provide knowledge beyond just a simple average or total.   To learn more about the value of these connections, sourcing accurate data, and how it is transformed into useful graphics, read the complete article and check out the case study used to convey the main points outlined above...  [...] [...] For many data visualization projects, information comes from a source that has already done some aggregation. This is both a blessing and a curse. Aggregation definitely simplifies the analysis and visualization process, but it can also greatly reduce the visualization and analysis options. This is because aggregation often destroys connections in data. For this reason, it's critical to have an in-depth and thorough knowledge and understanding of the information from aggregated information. There are several different visualization techniques that open up once we have the original data, such as Euler diagrams and parallel sets.   The extra information that can be obtained from visualizations is important to gaining a full understanding of the data, and it can lead to a much more interesting story, as well as far better visualizations and more accurate connections and links within those visualizations. So, when gathering data about something, remember to dig deeper into it, as there are many important connections that happen within data that can provide knowledge beyond just a simple average or total.   To learn more about the value of these connections, sourcing accurate data, and how it is transformed into useful graphics, read the complete article and check out the case study used to convey the main points outlined above…  [...]

]]> http://blog.visual.ly/connections-in-data/#comment-761 Visualizing Connections In Data & Analyzing Information | 21st Century skills of critical and creative thinking | Scoop.it Wed, 14 Nov 2012 22:06:21 +0000 http://blog.visual.ly/?p=7500#comment-761 [...] For many data visualization projects, information comes from a source that has already done some aggregation. This is both a blessing and a curse. Aggregation definitely simplifies the analysis and visualization process, but it can also greatly reduce the visualization and analysis options. This is because aggregation often destroys connections in data. For this reason, it's critical to have an in-depth and thorough knowledge and understanding of the information from aggregated information. There are several different visualization techniques that open up once we have the original data, such as Euler diagrams and parallel sets.   The extra information that can be obtained from visualizations is important to gaining a full understanding of the data, and it can lead to a much more interesting story, as well as far better visualizations and more accurate connections and links within those visualizations. So, when gathering data about something, remember to dig deeper into it, as there are many important connections that happen within data that can provide knowledge beyond just a simple average or total.   To learn more about the value of these connections, sourcing accurate data, and how it is transformed into useful graphics, read the complete article and check out the case study used to convey the main points outlined above...  [...] [...] For many data visualization projects, information comes from a source that has already done some aggregation. This is both a blessing and a curse. Aggregation definitely simplifies the analysis and visualization process, but it can also greatly reduce the visualization and analysis options. This is because aggregation often destroys connections in data. For this reason, it's critical to have an in-depth and thorough knowledge and understanding of the information from aggregated information. There are several different visualization techniques that open up once we have the original data, such as Euler diagrams and parallel sets.   The extra information that can be obtained from visualizations is important to gaining a full understanding of the data, and it can lead to a much more interesting story, as well as far better visualizations and more accurate connections and links within those visualizations. So, when gathering data about something, remember to dig deeper into it, as there are many important connections that happen within data that can provide knowledge beyond just a simple average or total.   To learn more about the value of these connections, sourcing accurate data, and how it is transformed into useful graphics, read the complete article and check out the case study used to convey the main points outlined above…  [...]

]]> http://blog.visual.ly/connections-in-data/#comment-760 Visualizing Connections In Data & Analyzing Information | information analyst | Scoop.it Wed, 14 Nov 2012 21:39:21 +0000 http://blog.visual.ly/?p=7500#comment-760 [...] For many data visualization projects, information comes from a source that has already done some aggregation. This is both a blessing and a curse. Aggregation definitely simplifies the analysis and visualization process, but it can also greatly reduce the visualization and analysis options. This is because aggregation often destroys connections in data. For this reason, it's critical to have an in-depth and thorough knowledge and understanding of the information from aggregated information. There are several different visualization techniques that open up once we have the original data, such as Euler diagrams and parallel sets.   The extra information that can be obtained from visualizations is important to gaining a full understanding of the data, and it can lead to a much more interesting story, as well as far better visualizations and more accurate connections and links within those visualizations. So, when gathering data about something, remember to dig deeper into it, as there are many important connections that happen within data that can provide knowledge beyond just a simple average or total.   To learn more about the value of these connections, sourcing accurate data, and how it is transformed into useful graphics, read the complete article and check out the case study used to convey the main points outlined above...  [...] [...] For many data visualization projects, information comes from a source that has already done some aggregation. This is both a blessing and a curse. Aggregation definitely simplifies the analysis and visualization process, but it can also greatly reduce the visualization and analysis options. This is because aggregation often destroys connections in data. For this reason, it's critical to have an in-depth and thorough knowledge and understanding of the information from aggregated information. There are several different visualization techniques that open up once we have the original data, such as Euler diagrams and parallel sets.   The extra information that can be obtained from visualizations is important to gaining a full understanding of the data, and it can lead to a much more interesting story, as well as far better visualizations and more accurate connections and links within those visualizations. So, when gathering data about something, remember to dig deeper into it, as there are many important connections that happen within data that can provide knowledge beyond just a simple average or total.   To learn more about the value of these connections, sourcing accurate data, and how it is transformed into useful graphics, read the complete article and check out the case study used to convey the main points outlined above…  [...]

]]> http://blog.visual.ly/connections-in-data/#comment-759 Visualizing Connections In Data & Analyzing Information | visual data | Scoop.it Wed, 14 Nov 2012 19:45:36 +0000 http://blog.visual.ly/?p=7500#comment-759 [...] For many data visualization projects, information comes from a source that has already done some aggregation. This is both a blessing and a curse. Aggregation definitely simplifies the analysis and visualization process, but it can also greatly reduce the visualization and analysis options. This is because aggregation often destroys connections in data. For this reason, it's critical to have an in-depth and thorough knowledge and understanding of the information from aggregated information. There are several different visualization techniques that open up once we have the original data, such as Euler diagrams and parallel sets.The extra information that can be obtained from visualizations is important to gaining a full understanding of the data, and it can lead to a much more interesting story, as well as far better visualizations and more accurate connections and links within those visualizations.So, when gathering data about something, remember to dig deeper into it, as there are many important connections that happen within data that can provide knowledge beyond just a simple average or total.To learn more about the value of these connections, sourcing accurate data, and how it is transformed into useful graphics, read the complete article and check out the case study used to convey the main points outlined above...  [...] [...] For many data visualization projects, information comes from a source that has already done some aggregation. This is both a blessing and a curse. Aggregation definitely simplifies the analysis and visualization process, but it can also greatly reduce the visualization and analysis options. This is because aggregation often destroys connections in data. For this reason, it's critical to have an in-depth and thorough knowledge and understanding of the information from aggregated information. There are several different visualization techniques that open up once we have the original data, such as Euler diagrams and parallel sets.The extra information that can be obtained from visualizations is important to gaining a full understanding of the data, and it can lead to a much more interesting story, as well as far better visualizations and more accurate connections and links within those visualizations.So, when gathering data about something, remember to dig deeper into it, as there are many important connections that happen within data that can provide knowledge beyond just a simple average or total.To learn more about the value of these connections, sourcing accurate data, and how it is transformed into useful graphics, read the complete article and check out the case study used to convey the main points outlined above…  [...]

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