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Data Visualization

 

Visualization allows us to analyse and understand data better. Visualizing moves past two-dimensional flatland lists, and encourages the exploration of data

By using visual elements like charts, graphs, and maps, data visualization is an accessible way to see and understand trends, outliers, and patterns in data.

If you plan to share your data, visualization will also allow you to get your story across much faster.

With Kounta Insights - Custom plan, you will have access to interactive data visualizations as you build your custom reports and dashboards.

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Whether you want to uncover hidden truths in your data or just looking to make it easier to view for the stakeholders of your business - or both - you can choose from various data vis options.

This guide covers the fundamentals of using data visualization to your advantage.

 


What’s in this guide?

 

Before you begin

Choose your data vis

Customise your data vis

Change the Colors

Remove the space-consuming decimal places

Axis Names and Value Labels

Remove the Axis Name

Remove the Axis Value Labels

Change the Axis Name

Add a Reference Line

Frequently Asked Questions

 


Before you begin

 

You would need:

 


Choose your data vis

 

Choosing the right data vis is vital to uncovering the story behind your data. Here are a few tips:

1. Data over time? Use Scatter Plot, Line, or Area

  • Single value dimensions (e.g. sales by month)

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  • Multi-value comparisons (e.g. sales and guest count by month)

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2. To show ranking? Use Bar or Column

  • Ranking one measure for one dimension set (eg: sales per month)

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  • Showing multiple measures (max 2 recommended) for one dimension (eg: sales and guest count per month)

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3. Percentages? Use Pie charts (eg: sales by product category)

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Customise your data vis

 

After choosing the data visualization for you, it’s easy to customise and finetune it. First, select Edit beside Visualization - you will then have the option to do the following:

 

Change the Colors

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1. Under Series select the Colors drop-down then choose from the themes.

2. Select Save

 

Remove the space-consuming decimal places

1. The Y axis contains the numerical values. This is the same for both bar and column. So go ahead and select Y

2. Enter this under the 'Value format' option: $#,##0

3. Select Save

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Axis Names and Value Labels

Note - These are the same steps for both the X and Y axis

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Remove the Axis Name

1. Select X or Y

2. Toggle Show Axis Name to OFF

3. Select Save

 

Remove the Axis Value Labels

1. Select X or Y

2. Simply toggle Axis Value Labels to OFF

3. Select Save

 

Change the Axis Name

1. Select X or Y

2. To change the axis name, first toggle Show Axis Name to ON.

3. Enter the new name on the provided field.

4. Select Save

 

Add a Reference Line

The reference line a great way to add perspective to the numbers on your Y axis. This can be a single value or range.

1. Select Y

2. Scroll down to MARKINGS and select Add Reference Line

3. Select the Type

Line - this shows a single value which can be the Median, Average, Maximum, or Minimum value of the data set - you can also enter a Custom value.

Range - when you choose this, you can choose a start and end value which both can be the Median, Average, Maximum, or Minimum value of the data set - or a Custom value

Line with Margins - the central value is the line -this can be the Median, Average, Maximum, or Minimum value of the data set - or a custom value. The margins appears above or below reflecting Standard Deviation or Variance - they can also be Custom values.

4. Select the values you would like your Line, Range, or Line with Margins to reflect

Line - select the value of the line

Range - select the start value and end value

Line with Margins - select the value of the line, the margin above, and the margin below

5. Select the label position

6. Finally select the color of the reference line

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Frequently Asked Questions

 

Are all data visualizations compatible with all kinds of data sets?

Depending on the data sets you’ve chosen, there will be compatible data visualization options. It is a general best practice not to overload your report with too many dimensions and measures as this will decrease the focus of the report and possibly reduce compatible data visualizations.

 

 


What's my next step?

 

Did you have trouble with any of the terminologies here? You may find our guide on terminologies useful.

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