Displaying Data in Charts

Your report is the gateway to insights and actionable information. Using the right charts means that your audience interprets data the right way and gets the right insights without any confusion. We broke them down into groups so you can identify the one that is most relevant depending on what you are trying to demonstrate.

You want to ask yourself a few questions before picking visualizations. These are examples that help you know why you might need a specific chart. Are you trying to compare values or analyze trends? Do you want to demonstrate the composition of a process or understand how your data is distributed? Do you want to highlight the relationship between several data subsets?

Charts are grouped by intentions and the type of analysis you want to run.

We broke them down in multiple groups to help you decide which ones are the most relevant to your needs.

Use these charts to view the differences between values.

It provides a simple comparison of categorical divisions of measures. It's the default analysis type.

For example, you could use a bar chart to compare the differences in your sales revenue between different countries.

Charts:

• Column, Bar, Dual Y-Axis Column, Dual Y-Axis Line, Combined Column Line, Dual Y-Axis Combined Column Line, 3D column, Waterfall

Use these charts to show a trend in the data values. This analysis type is particularly useful for dimensions that are time-based, such as Year. It's useful to see progression of your data and possible patterns.

For example, you can use a line chart to view sales revenue trends of a product throughout a range of years.

Charts:

• Line, Area

Use these charts to show the proportion of a value in a whole. For example, you could use a pie chart to show the proportion of each quarter in a full year of sales revenue.

Charts:

• Pie, Pie with Variable Slice Depth, Donut, Stacked Column, 100% Stacked Column, Stacked Bar, 100% Stacked Bar, Funnel, Pyramid

Use one of these charts to show a summarized group of unorganized data. You can also use them for qualitative and quantitative data.

Charts:

• Tree Map, Heat Map, Box Plot, Radar, Tag Cloud

Use these charts to view the relationship between values. It's useful for comparing multiple measure values.

For example, you can view the correlation of two measures, and understand the impact of the first measure on the second one.

Charts:

• Scatter Plot, Bubble, Polar Bubble, Polar Scatter Plot

Use these charts to show a map of the country object. The data for dimensions sorted by country are shown on the map. This is useful to see the geographical spread of data.

Charts:

• Geo Choropleth, Geo Bubble, Geo Pie

Use to show the value of a key performance indicator. For example, you could use a gauge chart to show the year-to-date sales revenue together with the sales revenue target for the year.

Charts:

• Speedometer, Linear Gauge, Angular Gauge, Tile, Deviation Tile

Geomaps display data on a geographic map.

Geomap charts are useful if you want to compare your data geographically. There is a geographical database embedded in Web Intelligence and a matching algorithm to automatically match values of dimensions, merged objects or dimension variables with a location. When you match values with specific locations, you geo-qualify the values and their parent object so they can be rendered on a map. The geo-qualification can be done using either the name of a location, or its latitude and longitude coordinates.

Geomaps rely on a geographical database to render your data.

Before you start using geomaps in you reports, you need to set up your data and go through the geo-qualification process so that the values can be bound to the geographical database. Geo-qualifying your data means that you match each value of an object with a specific location. Geomaps then use these locations to render your data on a map. The geo-qualification can be done using either the name of a location, or its latitude and longitude coordinates.

Web Intelligence uses an algorithm to match each value of the object with a geographic location. The search engine uses fuzzy logic to create three categories of values and automatically match them with locations:

• Resolved: only one location matches at 100%, and is automatically bound to the value.
• Unresolved: several locations match at 100% or higher than 85% but below 100%. There's no obvious match, and you have to select the most appropriate one.
• Missing: no location found, or locations match at lower than 85%. Search for the location you want to bind in the geographical database.

You may select a different location in the drop-down list from the one selected by the automatic matching mechanism.

Latitude and longitude coordinates are two objects that must be available as dimensions, dimensions' attributes or variables. They can be any object that can be added to a dimension as a detail, and do not necessarily have to be the same type of object. You can have latitude coordinates as a dimension and longitude coordinates as a variable, for instance. However, make sure they both have Number as data type.

You can change a table into a chart.

You can also change from one table type to another or change from one chart type to another.

In Design mode, select the table to convert. In the Feeding tab, in the Turn Into section, select the new table or chart type.