Task 1
What to doA file named people_and_society.tsv is provided with this task. It contains various statistical indicators about different countries. The TSV format is almost the same as CSV, but TSV uses a tab character (letter T) as the delimiter. The file people_and_society.tsv contains the following information:
country — the name of the country.
region — the name of the part of the world where the country is located.
median_age — the median age in the population.
birth_rate — birth rate (average number of births per year per 1,000 people).
death_rate — death rate (average number of deaths per year per 1,000 people).
life_expectancy — life expectancy in the country.
fertility_rate — fertility rate (average number of children per woman).
obesity_rate — obesity rate (percentage of the adult population of the country suffering from obesity).
Import the data from this file into Power BI. Note that in the median_age column, the # character is used as a decimal separator, so Power BI cannot automatically recognize it as a number. Additionally, there is an error in the region column with the value Evropa. The correct spelling is Europe. Correct these defects and load the data from the file into a Power BI project. Save the project in a file named bi_homework.pbix.
Task 2
What to doIn the previous task, you loaded a TSV file into Power BI. The data for this file was collected from the cia.gov website. In this task, we will continue working with data from cia.gov. Open the Power BI project bi_homework.pbix. Load the following data into Power BI from the additional materials:
Education Expenditures (education.csv): This table should have two columns: country and edu_of_gdp. Remove any extra columns and rename the remaining ones if necessary.
Military Expenditures (military.csv): This table should have two columns: country and military_of_gdp. Remove any extra columns and rename the remaining ones if necessary.
Unemployment rate (unemployment.csv): This table should have two columns: country and unemployment_rate.
Now establish relationships from the people_and_society table to the education, military, and unemployment tables using LEFT JOIN. Make sure to check the “use fuzzy matching” option. Save the project in the same file.
Task 3
What to doOpen the file with your project. Go to the report editor screen. Add the following widgets to the screen:
A card widget showing a single number — the number of countries in the people_and_society table.
A card widget showing a single number — the median age of the median ages of countries from the people_and_society table.
A card widget showing a single number — the maximum life expectancy from the people_and_society table.
A card widget showing a single number — the minimum life expectancy from the people_and_society table.
A bar chart showing the death rate for the top 10 countries with the highest death rates.
A bar chart showing the birth rate for the top 10 countries with the highest birth rates.
A clustered bar chart showing the fertility rate (fertility_rate) and education expenditures (edu_of_gdp) for the top 10 countries with the lowest education expenditures from the people_and_society table.
A clustered bar chart showing the fertility rate (fertility_rate) and education expenditures (edu_of_gdp) for the top 10 countries with the highest education expenditures from the people_and_society table. Note: if you do everything correctly, the highest bar on the chart will correspond to a country with no name (Blank). Think about why this happened and explain it in the input field under the task. Then create a filter for the widget to remove the bar for the unnamed country.
A table with the following columns:region from people_and_society
median_age from people_and_society
unemployment_rate from unemployment.
By default, Power BI will calculate the sum of the values for each region. Change this so that the columns show the median values for age and unemployment rate. Note: when you change the aggregation function, the columns will become “wider” because the column names will include the function name. Rename the columns back to median_age and unemployment_rate. Then remove the row where the part of the world is unnamed.
Save your project in the same file.
Task 4
What to doOpen the file with your project. Go to the report editor screen. The first page of the editor should be filled with the report you prepared in the previous task. So create a new, blank page.
Add the following widgets to the blank page:
A map widget. Use country names as locations and military expenditures from the military table as the size of the circles.
A filled map widget, which colors entire areas based on the value of a parameter. In our case, the area is the country. Configure the country’s color: the darker it is, the higher the percentage of the population suffering from obesity. Use gradient fill. If you can’t figure it out on your own, Google for instructions and tutorials. After coloring the map, configure the tooltips so that when you hover over a country, a pop-up window appears next to the cursor with the country’s name and the percentage of obesity.
A slicer widget. Drag the region field from the people_and_society table into it. Configure a filter for the widget to exclude the unnamed country (Blank). Click the checkboxes in the widget and make sure the map display changes depending on the selected country.
Save the project in the same file.
Task 5
What to doOpen the file with your project in Power BI. Go to the report screen and create a new, third page. Add a scatter plot widget to the blank page. This chart helps to see the functional dependence of one numerical variable on another. Set the fertility rate from the people_and_society table on the Y-axis and the median age from the same table on the X-axis. In the field settings on the axes (click the checkmark to the right of the field), select “Don’t Summarize” for both the fertility_rate and median_age fields. If you do everything correctly, the points will almost line up, indicating an obvious functional dependence. Think about what this chart means and explain it in the input field under the task.
Save the project in the same file.
Evaluation Criteria
We will not evaluate the visual style of your reports — how neatly the widgets are aligned on the screen. The main points are:
Data is loaded correctly.
The report uses the required fields.
The text answers to the questions are coherent and understandable.
How to submit your work for review
Send me the resulting file bi_homework.pbix with three report pages through the form below.
Write the answers to the two questions about the nature of the data on which you will build the reports directly in the form.
Below are all files that you need

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Power BI Data Analysis appeared first on academicassistpro.

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