Data Visualization and Reporting
Data is not meaningful unless people can understand
it. Collecting and analyzing data are not enough, data has to be presented to
concerned parties. That is the reason data visualization is such important. Here are seven key tips to help turn data into
insights people will understand:
1. Keep the audience and their information needs in mind.
We have to know who our target audience is and find out good ways to present to them. It is vital to customize any data visualization to meet the audience and their information needs. Think of who is in that audience and then think about the questions they would like answered. Knowing what we are addressing help us select right data out of tons of data and make it meaningful to audience.
We have to know who our target audience is and find out good ways to present to them. It is vital to customize any data visualization to meet the audience and their information needs. Think of who is in that audience and then think about the questions they would like answered. Knowing what we are addressing help us select right data out of tons of data and make it meaningful to audience.
2. Choose
the right chart.
There are so many different types of charts available in the data visualization tools, such as bar chart, line graph, pie chart, etc. Bar chart might be the most common chart type. However, we need to choose the right type depends on what kinds of information because not all charts are created equal. Some do a better job than others at displaying different kinds of information. We need to choose the best chart type to display the information.
There are so many different types of charts available in the data visualization tools, such as bar chart, line graph, pie chart, etc. Bar chart might be the most common chart type. However, we need to choose the right type depends on what kinds of information because not all charts are created equal. Some do a better job than others at displaying different kinds of information. We need to choose the best chart type to display the information.
3. Go
beyond Excel or PowerPoint templates.
Speaking of data visualization, many people may first think of excel which is a very nice tool for visualizing data. But when it comes to big data, utilizing other great tools such as Tableau, Data Miner, would make the life easier. Another popular visualization tool is PowerPoint, but its built-in templates may not be doing your data any favors. Instead of trying to get fancy, keep your visualizations simple and uncluttered to be as clear as possible.
Speaking of data visualization, many people may first think of excel which is a very nice tool for visualizing data. But when it comes to big data, utilizing other great tools such as Tableau, Data Miner, would make the life easier. Another popular visualization tool is PowerPoint, but its built-in templates may not be doing your data any favors. Instead of trying to get fancy, keep your visualizations simple and uncluttered to be as clear as possible.
4. Provide context.
The purpose of data visualization is not only showing the data we have in our data base, but we need to use the data to have storytelling. Making good use of color, size and other visual cues to provide context and include short narratives that highlight the key insights. A good visualization will make the user understand what’s going go with the data, prompt the user to act on the data being presented, which may be deciding location on a new business, or may be about executing marketing campaign, or other important decisions making on company.
The purpose of data visualization is not only showing the data we have in our data base, but we need to use the data to have storytelling. Making good use of color, size and other visual cues to provide context and include short narratives that highlight the key insights. A good visualization will make the user understand what’s going go with the data, prompt the user to act on the data being presented, which may be deciding location on a new business, or may be about executing marketing campaign, or other important decisions making on company.
5. Direct people to the most important information.
A good data reporting should be able to draw people’s attention to significant points on information and lead people to get insights from the data presented. When designing data visualizations, use sensory details like color, size, fonts, and graphics to direct attention to the most important pieces of information would be a great idea.
A good data reporting should be able to draw people’s attention to significant points on information and lead people to get insights from the data presented. When designing data visualizations, use sensory details like color, size, fonts, and graphics to direct attention to the most important pieces of information would be a great idea.
6. Axis
labels and numbers should be clear.
Avoid fancy labels and gauges that can get in the way of clarity. Label the axis of a graph or chart clearly and start at zero—unless you have a strong reason not to—e.g. when all the data is clustered at much higher values.
Avoid fancy labels and gauges that can get in the way of clarity. Label the axis of a graph or chart clearly and start at zero—unless you have a strong reason not to—e.g. when all the data is clustered at much higher values.
7. Provide
interactivity when appropriate.
New generations of data-visualization tools make it possible to build interactivity into many visualizations that can benefit the end user. But again, remember that this isn’t a parlor trick, and should be used when interactivity can clarify, rather than confuse, the presentation of data.
New generations of data-visualization tools make it possible to build interactivity into many visualizations that can benefit the end user. But again, remember that this isn’t a parlor trick, and should be used when interactivity can clarify, rather than confuse, the presentation of data.
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