Indexing Dataset Collection

Tables

• Historical Index Data for 'Luke' Website from FinlandTSV

  This table contains the version history of the 'indeksit__fact' table rows, sourced from the web site of 'Luke' in Finland. It has additional columns compared to its base table, including '_start_date' and '_end_date'. The '_start_date' column indicates the date when each row was extracted from the data source, while the '_end_date' column indicates the date of extraction for the next version of the row. If the '_end_date' value is null, it means that the row is the most recent version. This historical data can be analyzed for a variety of purposes, such as tracking changes in 'kuukausi' (month), 'indeksi' (index), and 'indeksit' (indices) over time. Data analytics applications can utilize this table to identify trends, perform time-series analysis, and generate insights about the...

• Historical Versions of Monthly Indexes from Luke (Finland)TSV

  This table contains the version history of extracted rows from the 'Luke' data source's 'indeksitdim_kuukausi' table. Each row in this table represents a specific version of a row in the base table. The 'indeksitdim_kuukausi__history' table includes additional columns compared to the base table, such as '_start_date' and '_end_date', which indicate the extraction dates of each row version. If the '_end_date' column has a null value, it means that the row is the most recent version. This table sourced from the web site of 'Luke' from Finland (ISO country code: 'fi'). Examples of how this data can be utilized in data analytics include analyzing the historical changes in the 'code' and 'label' columns over time, identifying trends, and understanding the evolution of dimensions during...

• Indexes - FinlandTSV

  This table contains data from the 'Luke' website in Finland. It provides information about different indexes. The data in this table can be used for various data analytics purposes, such as: Analyzing trends and changes over time in index values. Assessing the impact of certain events or factors on index values. Comparing index values across different regions or categories. The table consists of columns such as '_extract_date', '_row_number', 'code', and 'label'. These columns contain specific information related to the indexes. By analyzing and interpreting the data in this table, valuable insights can be gained for informed decision-making and research purposes.

• Luke - Monthly Indexes of FinlandTSV

  This table contains data from the 'Luke' website, sourced from Finland. It consists of various indices related to different months. The data can be utilized in data analytics to analyze and compare trends in different indices over time, identify seasonal patterns, and assess the overall economic performance. By examining the values in the 'indeksi' and 'indeksit' columns, one can gain insights into the changes and fluctuations in various indices. Additionally, the 'kuukausi' column provides information on the specific month for each data point. The table also includes other columns like '_extract_date' and '_row_number' which can be used for data management and tracking purposes.

• Monthly Index Data for FinlandTSV

  This table contains monthly indices data from the website of the Natural Resources Institute Finland (Luke). The data originates from Finland (ISO country code 'fi'). The table includes information such as the extraction date, row number, code, and label. The data in this table can be utilized in various data analytics scenarios such as analyzing trends and patterns in monthly indices, comparing indices across different periods, and tracking changes in indices over time.

• Version History of the Indexes of Finland (Luke)TSV

  This table contains the version history of rows extracted from the 'Luke' website in Finland. It is a historical representation of the 'indeksit__dim_indeksi' table. Each row in this table represents a version of a particular index. The '_start_date' column indicates the date when the row was extracted, while the '_end_date' column indicates the date when a new version of the row was extracted. If the value of the '_end_date' column is null, it means that the row represents the most recent version of the data. The table provides a valuable resource for data analysis, allowing users to track changes in the index values over time. By comparing different versions of the data, users can analyze trends, identify anomalies, and gain insights into the dynamics of the indices. For example,...