Historical Version Records of the Sea-Extending Postal Code Areas (2015)

The 'table__history' is a comprehensive dataset that captures the version history of its base table rows. It's part of the dataset collection 'postialue_pno_meri_2015'. This data originates from the 'Paavo-postinumeroalueet (merialueille ulottuva) 2015', which translates to 'Paavo Postal Code Areas (extending to sea areas) 2015' in English. The table is sourced from the website of 'Tilastokeskus' (Statistics Finland) located in Finland.

The data in the table is organized into various columns, each with a unique identifier. For instance, the '_row_number' column captures the number of the row in the raw data extracted from the data source. Each row in this version history table is uniquely identified by a combination of the '_start_date' and '_row_number'.

The table also includes columns for '_start_date' and '_end_date', which represent the date when the row was extracted from the data source and the date when a new version of the row was extracted, respectively. If the '_end_date' is null, it indicates that the row is the most recent version.

Geographical data in the table is stored under columns beginning with 'geom_', which can be utilized for geospatial data analytics. This includes geographic coordinates presented using the WGS 84 coordinate reference system, with axis order longitude first, followed by latitude.

The table also includes data on various aspects like the name of the area, the postal code, the area in square meters, and the year. The data also includes identifiers for each row and geographical information about each area, such as the centroid and the center coordinates.

This dataset could be extremely useful for a variety of data analytics purposes. For instance, it could be used to track changes in geographical data over time, which could be useful in environmental studies or urban planning. It could also be used to analyze patterns in postal code distributions, which could be valuable for logistics or delivery companies. Furthermore, since the geographic coordinates are provided, it could be used in conjunction with other geospatial data for more complex analyses, such as studying population density in relation to geographical features.