Turkmenistan, Furniture Industry, Production, 1000 EUR, Value (Y)

Data Summary: Turkmenistan, Furniture Industry, Production, 1000 EUR, Trend + Forecast, Value (Y)

Time series data for Turkmenistan, Furniture Industry, Production, 1000 EUR, Trend + Forecast, Value (Y)
Time Period Value Data Range
2006 40.005,00 2002 - 2031
2007 64.202,00 2002 - 2031
2008 50.231,00 2002 - 2031
2009 55.678,00 2002 - 2031
2010 61.125,00 2002 - 2031
2011 66.572,00 2002 - 2031
2012 72.019,00 2002 - 2031
2013 77.466,00 2002 - 2031
2014 82.913,00 2002 - 2031
2015 97.622,00 2002 - 2031
2016 121.990,00 2002 - 2031
2017 141.235,00 2002 - 2031
2018 159.876,00 2002 - 2031
2019 176.856,00 2002 - 2031
2020 170.312,00 2002 - 2031
2021 173.718,00 2002 - 2031
2022 175.455,00 2002 - 2031
2023 161.419,00 2002 - 2031
2024 176.856,00 2002 - 2031
2025 179.130,87 2002 - 2031
2026 183.259,06 2002 - 2031

This dataset contains 21 data points spanning from 2006 to 2026.

Analysis dimensions: Region, Industry, Measure, Unit, Analysis.

Statistical summary: Minimum value 40,005.00, Maximum value 183,259.06, Average value 118,473.33.

The chart above illustrates a time series model generated by the Innomis Market Management Intelligence® platform.
It represents one of many analytic models and visualization options available in One Space®.

To discover how Innomis continuously delivers and transforms millions of data records into actionable intelligence — empowering faster understanding, better decisions, and stronger management actions — please contact us to schedule a personal demo.

Data Insights and Analysis

This comprehensive dataset spans 21 time periods from 2006 to 2026. The analysis reveals values ranging from 40,005.00 to 183,259.06, with an average value of 118,473.33.

The data shows an overall upward trend with a total change of 143,254.06 (358.1% increase) over the analyzed period.

Key analytical dimensions include: Turkmenistan, Furniture Industry, Production, 1000 EUR, Trend + Forecast, Value (Y). This multi-dimensional analysis provides comprehensive insights into the underlying data patterns and trends.