Agricultural Area Cultivated with the Same Crop by Region in Finland

Tables

• Agricultural Area Cultivated with the Same Crop by RegionTSV

  This table contains data from the agricultural sector in Finland. It provides information on the agricultural area cultivated with the same crop by region. The data includes details such as the extract date, row number, year, ELY centre, and additional information. The 'agricultural_area_cultivated_with_the_same_crop' column represents the area of agricultural land dedicated to specific crops in each region. This table can be utilized in various data analytics scenarios, such as studying trends in crop cultivation over time, analyzing regional differences in agricultural practices, and identifying patterns in crop production based on extract dates. The data is sourced from the website of 'Luke', which is the Natural Resources Institute Finland.

• Agricultural Area Cultivated with the Same Crop by Region InformationTSV

  This dataset provides information about the agricultural area cultivated with the same crop by region. It is sourced from the web site of Luke, which originates from Finland (country code: FI). The table contains data on the extract date, row number, code, and label. The data in this table can be utilized in various data analytics scenarios, such as analyzing the distribution of cultivated agricultural areas across different regions, identifying trends in crop cultivation over time, and comparing the cultivation patterns of different crops in specific regions.

• Agricultural Areas Cultivated with the Same Crop by Region in Ely CentreTSV

  This table contains information on agricultural areas cultivated with the same crop by region from the data source 'Luke'. The data is sourced from the website of Luke, which originates from the country Finland (ISO country code 'fi'). The table includes columns such as '_extract_date' which represents the date the data was extracted, '_row_number' indicating the row number of the data, 'code' representing the code of the region, and 'label' providing the label or name of the region. This table can be used for data analytics to analyze the distribution and trends of agricultural areas cultivated with the same crop across different regions in Finland.

• Crop Cultivated Area by Region and YearTSV

  This table contains data on the agricultural areas cultivated with the same crop by region and year in Finland. The data is sourced from the web site of Luke, which is a Finnish research institute focusing on natural resources and the bioeconomy.

• Version History of Agricultural Area Cultivated with the Same Crop by Region - Dimensional Information - Luke - FinlandTSV

  This table contains the version history of agricultural areas cultivated with the same crop by region, along with additional dimension information. The data in this table is sourced from the 'Luke' website, which originates from Finland (ISO country code 'fi'). It is a historical record of the cultivated agricultural areas, indicating the start and end dates of each version. The '_start_date' column shows the date when a particular version of the row was extracted from the data source, while the '_end_date' column indicates the date when a new version of the row was extracted. If the '_end_date' value is null, it means that the row is the most recent version. This table provides valuable data for various data analytics purposes, such as analyzing the changes in agricultural cultivation...

• Version History of Agricultural Area Cultivated with the Same Crop by Region and Year - Luke (Finland)TSV

  This table contains the version history of the base table 'agricultural_area_cultivated_with_the_same_crop_by_region__dim_year'. It tracks the changes made to the base table rows over time. The table includes columns for '_start_date' and '_end_date', which indicate the start and end dates of each version of the rows. Additionally, the table has columns for '_row_number', 'code', and 'label'. While the table does not provide a description of these individual columns, it can be utilized in data analytics to analyze the historical changes in agricultural area cultivated with the same crop by region and year. For example, it can be used to track trends and patterns in agricultural practices across different regions and years. The data in this table is sourced from the web site of 'Luke',...

• Version History of Agricultural Area Cultivated with the Same Crop by Region Fact (Luke - Finland)TSV

  This table contains the version history of the rows in the 'agricultural_area_cultivated_with_the_same_crop_by_region__fact' table. The rows in this table represent the agricultural area cultivated with the same crop by region and its historical changes over time. Each row has two additional columns compared to the base table: '_start_date' and '_end_date', which indicate the period when the row was extracted from the source. If the '_end_date' column has a null value, it signifies that the row is the most recent version. The table's data is sourced from Luke, which is an agricultural research organization in Finland (ISO country code: FI). The data in this table can be utilized for various data analytics purposes, such as analyzing trends in agricultural area cultivated with the same...

• Version History of Agricultural Area Cultivated with the Same Crop by Region in Ely Centre from Luke (Finland)TSV

  This table contains the version history of the rows from the 'agricultural_area_cultivated_with_the_same_crop_by_region__dim_ely_centre' table. It includes additional columns '_start_date' and '_end_date' to indicate the extraction dates of each row. The data in this table is sourced from the 'Luke' website, which originates from Finland (ISO country code: 'fi'). The table can be utilized in data analytics to track changes in the agricultural areas cultivated with the same crop by region over time. By analyzing the start and end dates, trends and patterns in agricultural cultivation can be identified. This information can be valuable for studying the evolution of crop cultivation practices, understanding regional variations, and predicting future crop trends.