Version History of Major Regions 2016 (1:1 000 000)

The 'table__history' is a historical data repository of its base table. The table is part of a larger dataset collection that harbors related data tables. This particular table encapsulates the version history of its base table, tracking each modification to the table rows over time. The table is sourced from the 'Tilastokeskus' website based in Finland. The contents of the table are described as 'Suuralueet 2016 (1:1 000 000)', which translates to 'Large areas 2016 (1:1 000 000)' in English. This indicates that the data is relevant to large geographical areas as of the year 2016.

The table is organized into several columns each with a unique purpose. Two of these columns, '_start_date' and '_end_date', are unique to this history table and are used to mark the lifespan of each row in the table. The '_start_date' marks when a row was added to the table and the '_end_date' signifies when a newer version of the row was added. If the '_end_date' of a row is null, it indicates that the row is the most recent version. Each row in the table is uniquely identified by a combination of the '_start_date' and '_row_number' columns, with the latter indicating the position of the row in the raw data.

The table also contains multiple 'geom_' prefixed columns which hold geographical data. This includes geographic coordinates, presented using the WGS 84 coordinate reference system with the longitude listed before the latitude. The 'geom_geotext' and 'geom_geojson' columns provide geographic data in text and JSON formats respectively. The 'geom_type' describes the type of the polygon representing the geographical area, while the 'geom_centroid' marks the geometric center of the area. The 'geom_center_x' and 'geom_center_y' provide the x and y coordinates of the center respectively.

Additional columns include 'name', 'namn', and 'nimi' which provide the name of the region in different languages. The 'suuralue' column provides a unique identifier for each large area, and 'vuosi' indicates the year of the data.

The richness of the data in this table makes it invaluable for various analytical purposes. For instance, the geographical data can be utilized for geospatial data analytics to visualize regional trends or patterns. The historical data can also be used to track changes in the regions over time, enabling longitudinal studies or retrospective analyses. Further, the multilingual name data can facilitate research across different linguistic or cultural contexts.