Version History of Postal Code Areas 2022

The 'table__history' is a comprehensive collection of data that provides a rich history of its base data rows. It is part of the 'postialue_pno_2022' dataset, which signifies its connection with postal area data. Specifically, this history table contains the version history of the Paavo postal code areas for the year 2022, a resource sourced from the 'Statistics Finland' website (Tilastokeskus) in Finland. The table includes a variety of columns that carry significant data, which can be utilized for various data analytics purposes.

One key aspect of this table is its ability to track changes over time. This is facilitated by the '_start_date' and '_end_date' columns, which respectively record the date when a row was extracted from the data source and the date when a new version of that row was extracted. The '_row_number' column, in combination with the '_start_date', serves to uniquely identify each row in this version history table. If the '_end_date' for a row is null, it signifies that the row is the most recent version.

A distinctive feature of this table is the inclusion of geographic data within the columns starting with 'geom_'. These contain geographic information that can be used for geospatial data analytics. The geographic coordinates are represented using the WGS 84 coordinate reference system, where the axis order is longitude first, followed by latitude.

The table records information about different postal areas, including their names, area coverage, unique identifiers, and more. For instance, it includes columns that contain the name of the postal area in two representations, the area size, and the year it represents. It also tags each row with a unique object ID.

This data can be instrumental in several data analytics applications. For instance, utilizing the geospatial data, analysts can perform geographic trend analysis or visualize the data on a map to identify patterns. The historical data can be used to track changes in the postal areas over time, enabling retrospective studies or predictive modeling. Moreover, the postal area data can be used to enhance demographic studies or market segmentation in Finland.