OLAP multi-dimensional databases allow users to view data from different angles, and likewise, it allows users to view data from different granularities. Users can use the Roll-Up function of multidimensional databases to view aggregate data, or they can use the Drill-Down function to view detailed data.
You can execute the following MDX querying statement, which queries turnover by years and specific aircraft types.
select
{ Date.[ALL].[2020], Date.[ALL].[2021], Date.[ALL].[2022] } on rows,
{
[Aircraft Type].[ALL].[Boeing].[Boeing 747],
[Aircraft Type].[ALL].[Boeing].[Boeing 777],
[Aircraft Type].[ALL].[Boeing].[Boeing 787 Dreamliner],
[Aircraft Type].[ALL].[Airbus].[Airbus A380],
[Aircraft Type].[ALL].[Airbus].[Airbus A350],
[Aircraft Type].[ALL].[Airbus].[Airbus A330]
} on columns
from [Airline Turnover];
If you no longer care about the annual turnover of each specific aircraft model, but want to check the turnover by aircraft manufacturer, you can do Roll-Up in the aircraft type dimension, modify the MDX as follows and execute.
The turnover corresponding to each aircraft manufacturer is aggregated by the specific aircraft type under it.
select
{ Date.[ALL].[2020], Date.[ALL].[2021], Date.[ALL].[2022] } on rows,
{
[Aircraft Type].[ALL].[Boeing],
[Aircraft Type].[ALL].[Airbus]
} on columns
from [Airline Turnover];
Next, if you want to drill-down in the aircraft type dimension to see the turnover generated by each aircraft manufacturer's aircraft types in each quarter of 2022, modify the MDX as follows and execute.
select
{ Date.[ALL].[2022].Q1, Date.[ALL].[2022].Q2, Date.[ALL].[2022].Q3, Date.[ALL].[2022].Q4 } on rows,
{
[Aircraft Type].[ALL].[Boeing],
[Aircraft Type].[ALL].[Airbus]
} on columns
from [Airline Turnover];