Time Available: 2002 - 2031
Data Summary: Austria, Exports to, Germany, Wood Processing Equipment, 1000 EUR, Trend + Forecast, Value (Y)
| Time Period | Value | Data Range |
|---|---|---|
| 2006 | 104.902,24 | 2002 - 2031 |
| 2007 | 116.407,10 | 2002 - 2031 |
| 2008 | 110.916,85 | 2002 - 2031 |
| 2009 | 92.144,28 | 2002 - 2031 |
| 2010 | 98.287,24 | 2002 - 2031 |
| 2011 | 110.956,57 | 2002 - 2031 |
| 2012 | 114.570,09 | 2002 - 2031 |
| 2013 | 109.160,64 | 2002 - 2031 |
| 2014 | 118.294,05 | 2002 - 2031 |
| 2015 | 112.570,38 | 2002 - 2031 |
| 2016 | 142.697,47 | 2002 - 2031 |
| 2017 | 138.945,69 | 2002 - 2031 |
| 2018 | 152.769,06 | 2002 - 2031 |
| 2019 | 157.327,71 | 2002 - 2031 |
| 2020 | 159.538,82 | 2002 - 2031 |
| 2021 | 194.220,95 | 2002 - 2031 |
| 2022 | 183.036,41 | 2002 - 2031 |
| 2023 | 213.621,11 | 2002 - 2031 |
| 2024 | 196.411,82 | 2002 - 2031 |
| 2025 | 160.030,33 | 2002 - 2031 |
| 2026 | 157.779,82 | 2002 - 2031 |
This dataset contains 21 data points spanning from 2006 to 2026.
Analysis dimensions: Selected Competitor, Trade Flow, Market, Product, Unit, Analysis.
Statistical summary: Minimum value 92,144.28, Maximum value 213,621.11, Average value 140,218.51.
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It represents one of many analytic models and visualization options available in One Space®.
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- Solution
- Global Export Sales Intelligence
- Selected Competitor
- Austria
- Trade Flow
- Exports to
- Market
- Germany
- Product
- Wood Processing Equipment
- Unit
- 1000 EUR
- Analysis
- Value (Y)
- TIME (Displayed)
- 2006 - 2026
- TIME (Available)
- 2002 - 2031
Data Insights and Analysis
This comprehensive dataset spans 21 time periods from 2006 to 2026. The analysis reveals values ranging from 92,144.28 to 213,621.11, with an average value of 140,218.51.
The data shows an overall upward trend with a total change of 52,877.58 (50.4% increase) over the analyzed period.
Key analytical dimensions include: Austria, Exports to, Germany, Wood Processing Equipment, 1000 EUR, Trend + Forecast, Value (Y). This multi-dimensional analysis provides comprehensive insights into the underlying data patterns and trends.