Data visualization is a crucial step in using Data Vault. Integration with BI tools such as Power BI allows business users to quickly and intuitively access information, analyze it, and make decisions.

Steps for Power BI Integration

1. Connecting to Data Vault

Power BI allows connecting to Data Vault through various data sources such as SQL Server, Azure SQL Database, Snowflake, and others.

Example:
To connect to a SQL Server database:

  1. In Power BI, select Get Data → SQL Server.
  2. Specify the server and database where your Data Vault tables (Raw Vault, Business Vault, or Data Marts) are located.
  3. Click Load to load the data or Transform Data for preprocessing.

2. Creating a Data Model

After loading data into Power BI, it is important to correctly set up relationships between tables.

Example:
In a Data Mart for flight load analysis:

  • Fact table: FlightLoad
  • Dimensions: Dim_Flights, Dim_Dates

Steps:

  1. Go to the Model tab in Power BI.
  2. Ensure the tables are linked:
    • FlightLoad.FlightID → Dim_Flights.FlightID
    • FlightLoad.Date → Dim_Dates.Date

3. Building Visualizations

BI tools like Power BI provide numerous visualizations: charts, graphs, maps, and tables.

Example 1: Flight load analysis by day of the week

  1. Add a Bar Chart.
  2. Add the DayOfWeek field from the Dim_Dates table to the X-axis.
  3. Add AvgPassengers from FlightLoad to the Values.
  4. Configure sorting by the average number of passengers.

Result:
The chart will show which days of the week flights are most loaded.

Example 2: Geographic flight analysis

  1. Add a Map chart.
  2. Use the Origin and Destination fields from the Dim_Flights table to display departure and destination points.
  3. Set the point size based on the number of passengers (TotalPassengers).

Result:
The map will show which routes are the most popular.

Dashboard Implementation in Power BI

Key Elements:

  1. Key Metrics:
    • Total flight load.
    • Average flight load by day of the week.
  2. Charts:
    • Bar charts for analyzing load by airlines.
    • Line graphs for analyzing flight load trends over time.
  3. Maps:
    • Geographic distribution of flights.

Example Dashboard:

  1. Top Block:
    Cards with KPIs:

    • Total Passengers: 15,000
    • Avg Flight Load: 120
    • Top Airline: Delta

  2. Central Block:

    • Bar chart: load by day of the week.
    • Line graph: load trend by month.

  3. Bottom Block:

    • Map with routes and flight load.

Example SQL Queries for Power BI

1. Average Flight Load by Day of the Week:

SELECT 
    DD.DayOfWeek, 
    AVG(FL.TotalPassengers) AS AvgPassengers
FROM 
    FlightLoad FL
JOIN 
    Dim_Dates DD ON FL.Date = DD.Date
GROUP BY 
    DD.DayOfWeek
ORDER BY 
    AvgPassengers DESC;

2. Total Load by Airlines:

SELECT 
    DF.Airline, 
    SUM(FL.TotalPassengers) AS TotalPassengers
FROM 
    FlightLoad FL
JOIN 
    Dim_Flights DF ON FL.FlightID = DF.FlightID
GROUP BY 
    DF.Airline
ORDER BY 
    TotalPassengers DESC;

Benefits of Power BI Integration with Data Vault

  1. Flexibility:
    Ability to quickly adapt visualizations to changing business requirements.
  2. Dynamic Reports:
    Users can filter and explore data without the need to modify queries.
  3. Data Traceability:
    Thanks to the Data Vault structure, Power BI can organize drill-through from KPIs to raw data.

Conclusion

Integrating Data Vault with Power BI allows for effective use of data for business analysis. Building user-friendly and informative dashboards helps companies make decisions based on accurate and up-to-date data. Proper design of data marts and visualization setup enhances productivity and transparency in analytics.