Documentation - a space containing main files from the Training Course's activities, as well as a detailed guide of the main tool used.

1. General Navigation

• Home: Contains quick access to common tasks like getting data, creating visuals, and sharing reports.

• View: Switch between different views (Report, Data, Model) and adjust display settings.

• Insert: Add various elements to your report, such as visuals, buttons, and text boxes.

• Modeling: Access tools for managing relationships, creating measures, and working with DAX.

• Help: Access tutorials, documentation, and support resources.

2. Importing Data

1. Click "Get Data" on the Home ribbon.

2. Choose your data source (e.g., Excel, SQL Server, Web).

3. Select the specific tables or views you want to import.

4. Choose to load the data directly or transform it in Power Query Editor.

5. If loading directly, the data will appear in the Fields pane.

3. Formatting in Power Query

• Access Power Query Editor by selecting "Transform Data" when importing.

• Use the ribbon to apply various transformations:

  • Remove columns, rows, or errors

  • Change data types

  • Split or merge columns

  • Pivot or unpivot data

  • Create custom columns using M formula language

• Apply steps are recorded and can be modified or reordered in the Query Settings pane.

• Close and Apply to load the transformed data into Power BI.

4. Table View

• Access via the Data view button on the left sidebar.

• Displays data in a tabular format.

• Use to:

  • Check data accuracy

  • Add or remove columns

  • Change data types

  • Create calculated columns

  • Sort and filter data

5. Model View

• Access via the Model view button on the left sidebar.

• Displays tables and their relationships.

• Use to:

  • Create, modify, or delete relationships between tables

  • Adjust cardinality and cross-filter direction

  • Organize tables into display folders

  • Set up role-playing dimensions

6. Data

• In Report view, the Data pane is on the right side.

• Contains all imported tables and fields.

• Drag and drop fields onto the canvas to create visuals.

• Right-click fields to:

  • Create quick measures

  • Change summarization type

  • Add to filters

  • Create hierarchies

7. Filters

• Located in the Filters pane on the right side of Report view.

• Types of filters:

  • Visual level: Apply to a single visual

  • Page level: Apply to all visuals on the current page

  • Report level: Apply to all pages in the report

  • Drillthrough: Filter other report pages based on the current selection

• Can be configured as:

  • Basic

  • Advanced (using DAX expressions)

  • Top N

  • Relative Date

8. Format

• Access the Format pane by selecting a visual and clicking the paint roller icon.

• Use to customize:

  • Colors and fonts

  • Titles and labels

  • Data labels

  • Axes and legends

  • Backgrounds and borders

  • Conditional formatting

9. Slicers

• Special visuals that act as interactive filters.

• To create:

  • Click the Slicer icon in the Visualizations pane

  • Drag a field into the slicer

• Types:

  • List

  • Dropdown

  • Between (for numeric ranges)

  • Date range

• Formatting options:

  • Orientation (vertical/horizontal)

  • Single/multi-select

  • Visual style (tiles, buttons)

  • Sync slicers across pages

10. Measures

• Created in the Report view or Model view.

• Use DAX (Data Analysis Expressions) language.

• Dynamically calculate values based on other fields and measures.

• Key points:

  • Don't store values in the data model

  • Recalculate based on user interactions and filters

  • Can be used across multiple visuals and reports

  • Create by clicking "New Measure" in the Home tab

  • Use for complex calculations and KPIs

• Common functions:

  • SUM, AVERAGE, COUNT

  • TIME INTELLIGENCE (PREVIOUSYEAR, TOTALYTD)

  • CALCULATE for context modification

11. Calculated Columns

• Created in Data view or Model view.

• Also use DAX language.

• Generate a new column in an existing table.

• Key points:

  • Store values for each row in the data model

  • Calculate once and don't respond to user interactions

  • Use for row-by-row calculations

  • Create by clicking "New Column" in the Table tools

  • Useful for categorization or simple row-level computations

• Common uses:

  • Concatenating text fields

  • Creating age groups or price bands

  • Deriving dates (e.g., extracting year from a date)

  • Simple IF statements for categorization

Remember to use measures for aggregations and calculations that need to respond to user interactions, and calculated columns for stable, row-level computations. Both are powerful tools for enhancing your data model and creating insightful reports.

Important: save your work regularly and publish to the Power BI service when ready to share your report with others.

1. General Navigation

The Power BI interface offers intuitive access to key features through its ribbon tabs.

Example Scenario: You're a data analyst for a European youth NGO. You use the Home tab to create a new report on Erasmus+ participation. On the Insert tab, you add maps to visualize participant countries and bar charts for exchange durations. Using the Modeling tab, you create calculated measures for participation rates. On the View tab, you enable the Sync Slicers pane to ensure consistent filtering across multiple report pages, allowing for coherent analysis of youth mobility trends across different EU regions. 

2. Importing Data

Importing data is the first step in any Power BI project, often involving multiple sources.

Example Scenario: You're analyzing youth employment data across the EU. You download CSV files from the Eurostat website, then use "Get Data" in Power BI to import these files. You select the relevant tables and choose to transform the data in Power Query Editor.

3. Formatting in Power Query

Power Query Editor allows for data cleaning and shaping before analysis.

Example Scenario: With Erasmus+ participation data, you:

1. Remove columns with sensitive information

2. Convert 'Exchange Start Date' from text to date type

3. Split 'Host Country and City' into separate columns

4. Create a custom 'Exchange Duration (Months)' column

5. Filter out rows with incomplete program information

4. Table View

Table View provides a spreadsheet-like interface for data examination.

Example Scenario: In your Eurostat youth employment dataset, you:

1. Verify unemployment rates are correctly imported as percentages

2. Add a calculated column for 'Employment Rate'

3. Sort data by country and year to see trends

4. Filter to show only 18-25 age group data

5. Hide columns with provisional data

5. Model View

Model View is crucial for setting up relationships between tables.

Example Scenario: Working with EU youth programs datasets, you:

1. Create a relationship between 'Erasmus+ Participants' and 'EU Countries' tables

2. Set up a many-to-one relationship from 'Participants' to 'Programs'

3. Implement a role-playing dimension for application and program start dates

4. Organize dimension tables into a 'Dimensions' display folder

6. Data

The Data pane in Report view is your palette for creating visuals and analyses.

Example Scenario: Building a dashboard on EU youth volunteer activities, you:

1. Create a card visual for 'Total Volunteers'

2. Add a quick measure for 'Year-over-Year Growth in Volunteering'

3. Set 'Activity Date' summarization to 'Quarter' for trend analysis

4. Create a Location hierarchy: EU Region > Country > City

5. Add 'Volunteer Age Group' to the filters pane

7. Filters

Filters allow focusing on specific subsets of data, enhancing interactivity.

Example Scenario: For an Erasmus+ program analysis report, you set up:

1. A visual level filter for top 10 host countries by participant count

2. A page level filter for a specific academic year

3. A report level filter to exclude cancelled exchanges

4. A relative date filter for the last 12 months of data

5. An advanced filter for programs with >90% satisfaction rate

8. Format

The Format pane allows customization of visuals and reports.

Example Scenario: Polishing a youth unemployment rates chart, you:

1. Change colors to match EU flag (blue and yellow)

2. Increase font size of country names

3. Add title "Youth Unemployment Rates in EU Member States"

4. Show data labels on bars for precise values

5. Use conditional formatting to highlight below-average rates in green

9. Slicers

Slicers are interactive filtering tools that enhance user experience.

Example Scenario: Creating a dashboard for NGO youth program funding, you:

1. Add a list slicer for 'Program Type' (Education, Health, Employment)

2. Create a dropdown slicer for 'EU Region'

3. Implement a date range slicer for 'Funding Period'

4. Format 'Program Type' as horizontal tiles

5. Sync 'Funding Period' slicer across all report pages

10. Measures

Measures are DAX calculations that perform aggregate calculations across multiple rows of a table.

Example Scenario: For a youth employment analysis, you create measures:

1. 'Average Youth Unemployment Rate' = AVERAGE('Employment Data'[Unemployment Rate])

2. 'Total Youth Population' = SUM('Population Data'[Youth Count])

3. 'Employment Rate' = 1 - [Average Youth Unemployment Rate]

4. 'Year-over-Year Change' = [This Year's Rate] - [Last Year's Rate]

5. 'Countries Above Average' = COUNTAX(FILTER(ALL('Country Data'), [Country Rate] > [Average Rate]), 'Country Data'[Country])

11. Calculated Columns

Calculated columns are DAX expressions that compute a value for each row in a table.

Example Scenario: Enhancing your Erasmus+ participant data, you add calculated columns:

1. 'Age Group' = SWITCH(TRUE(), 'Participants'[Age] <= 24, "18-24", 'Participants'[Age] <= 30, "25-30", "30+")

2. 'Program Duration (Months)' = DATEDIFF('Participants'[Start Date], 'Participants'[End Date], MONTH)

3. 'Mobility Type' = IF('Participants'[Program Duration (Months)] <= 2, "Short-term", IF('Participants'[Program Duration (Months)] <= 12, "Long-term", "Extended"))

4. 'Funding Category' = SWITCH(TRUE(), 'Participants'[Funding Amount] < 2500, "Standard", 'Participants'[Funding Amount] < 7500, "Enhanced", "Special Needs")

5. 'Academic Year' = "AY " & IF(MONTH('Participants'[Start Date]) < 9, YEAR('Participants'[Start Date]) - 1, YEAR('Participants'[Start Date])) & "-" & IF(MONTH('Participants'[Start Date]) < 9, YEAR('Participants'[Start Date]), YEAR('Participants'[Start Date]) + 1)

Important: Remember to save your work regularly.