# Reporting with Power BI

## 📃 ngSurvey template 

![](/files/-MHlFDFc5k9FuXXRqwaS)

This is the template with questions we have used to create a report

{% hint style="info" %}
The respondents answers that are shown here are not real and were generated particularly for this walkthough
{% endhint %}

## 📈 ngSurvey report example

Here you can see the data report by each question of the template we used.

![](/files/-MHlIoSa70ehS4Vxosfj)

We have 930 unique respondents from 33 countries

![](/files/-MHlLbF-aVp8F6EiXf6r)

According to the answers you can see, for example, in which area how many people plan to use the survey

![](/files/-MHpPcOnR2cUwDNRcttX)

The level of preference is shown by each grade (from 0 to 10) and as the average level of preference of a total amount respondents, which is equal here 5.6 out of 10.

## 📊 Power BI report example

To create a more comprehensive cross-data report, based on the data from the survey, we have chosen as a value question the question **"How likely you will recommend our service to your friends and colleagues?"** to monitor the results according to the:‌

1. **Country** ("Where are you from?")
2. **Age (**"How old are you?")
3. **Education** ("What is your educational background?")
4. **Area of use** ("In which are do you plan to use your survey?")

![](/files/-MHpY5WSz7HSz-K2FcsY)

![](/files/-MHpfUttbifkQIKPaAzt)

![](/files/-MHpj3WCkVWX81ajco0C)

![](/files/-MHphQ07pEoeyAhOwSsG)

1. There are 930 unique respondents
2. The average result to the question "How likely you will recommend our service to your friends and colleagues?" is 5,59 out of 10
3. This **treemap** shows the level of preference according to the country of the respondent. The higher the level of preference the bigger the block
4. The **line chart** displays the average result of the level of preference according to the age and educational background. It is performed in 4 groups according to the age of the respondents that include 5 variants of educational background
5. The **area of use** slicer allows to see the results separately, according to each area. For example all the results of the respondents who plan to use their survey in Science.


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