65 datasets found
  1. T

    Steel - Price Data

    • tradingeconomics.com
    • ru.tradingeconomics.com
    • +13more
    csv, excel, json, xml
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    TRADING ECONOMICS, Steel - Price Data [Dataset]. https://tradingeconomics.com/commodity/steel
    Explore at:
    xml, csv, excel, jsonAvailable download formats
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Mar 27, 2009 - Sep 2, 2025
    Area covered
    World
    Description

    Steel rose to 3,076 CNY/T on September 2, 2025, up 0.89% from the previous day. Over the past month, Steel's price has fallen 3.78%, but it is still 1.02% higher than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Steel - values, historical data, forecasts and news - updated on September of 2025.

  2. Manufacturing Data | Electrical, Electronic & Industrial Manufacturing...

    • datarade.ai
    Updated Jan 1, 2018
    + more versions
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    Success.ai (2018). Manufacturing Data | Electrical, Electronic & Industrial Manufacturing Leaders Globally | Verified Global Profiles from 700M+ Dataset [Dataset]. https://datarade.ai/data-products/manufacturing-data-electrical-electronic-industrial-manu-success-ai
    Explore at:
    .bin, .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset updated
    Jan 1, 2018
    Dataset provided by
    Area covered
    Madagascar, Oman, Estonia, India, Mali, Suriname, State of, South Georgia and the South Sandwich Islands, Sint Eustatius and Saba, Malaysia
    Description

    Success.ai’s Manufacturing Data for Electrical, Electronic & Industrial Manufacturing Leaders Globally delivers a robust dataset designed to empower businesses in connecting with decision-makers in the global manufacturing sector. Covering professionals and leaders in electrical, electronic, and industrial manufacturing, this dataset offers verified contact details, firmographic insights, and actionable professional data.

    With access to over 700 million verified global profiles and insights from 70 million businesses, Success.ai ensures your outreach, market research, and business development efforts are powered by accurate, continuously updated, and AI-validated information. Backed by our Best Price Guarantee, this solution is essential for navigating the competitive manufacturing industry.

    Why Choose Success.ai’s Manufacturing Data?

    1. Verified Contact Data for Targeted Outreach

      • Access verified work emails, phone numbers, and LinkedIn profiles of executives, operations leaders, and engineers in the electrical, electronic, and industrial manufacturing industries.
      • AI-driven validation ensures 99% accuracy, optimizing communication efforts and improving campaign efficiency.
    2. Comprehensive Coverage of Global Manufacturing Leaders

      • Includes profiles from major manufacturing hubs across North America, Europe, Asia-Pacific, and other key regions.
      • Gain insights into operational practices, supply chain dynamics, and technological trends shaping the industry.
    3. Continuously Updated Datasets

      • Real-time updates capture changes in leadership, business expansions, and emerging market opportunities.
      • Stay aligned with evolving market conditions to capitalize on new opportunities effectively.
    4. Ethical and Compliant

      • Fully adheres to GDPR, CCPA, and other global privacy regulations, ensuring responsible use and compliance with legal standards.

    Data Highlights:

    • 700M+ Verified Global Profiles: Connect with industry leaders, engineers, and decision-makers in the electrical, electronic, and industrial manufacturing sectors.
    • 70M Business Profiles: Access detailed firmographic data, including company sizes, revenue ranges, and geographic footprints.
    • Decision-Maker Contacts: Engage with CEOs, operations managers, and procurement leads driving manufacturing strategies.
    • Industry Insights: Understand trends in automation, supply chain optimization, and emerging technologies.

    Key Features of the Dataset:

    1. Leadership and Decision-Maker Profiles

      • Identify and connect with professionals responsible for engineering, production, and operational excellence in the manufacturing sector.
      • Target decision-makers driving innovation, vendor selection, and manufacturing efficiency.
    2. Advanced Filters for Precision Campaigns

      • Filter companies by industry focus (electrical, electronic, industrial), geographic location, revenue size, or workforce composition.
      • Tailor campaigns to address specific challenges, such as cost reduction, sustainability, or digital transformation.
    3. Firmographic and Geographic Insights

      • Access detailed business information, including operational scopes, manufacturing capacities, and regional distribution.
      • Pinpoint key players in emerging and established manufacturing hubs for strategic engagement.
    4. AI-Driven Enrichment

      • Profiles enriched with actionable data allow for personalized messaging, highlight unique value propositions, and improve engagement outcomes with manufacturing stakeholders.

    Strategic Use Cases:

    1. Sales and Vendor Development

      • Offer tools, technologies, or raw materials tailored to the needs of manufacturers in the electrical, electronic, and industrial sectors.
      • Build relationships with procurement teams and operations managers seeking reliable suppliers or innovative solutions.
    2. Market Research and Competitive Analysis

      • Analyze global manufacturing trends, from automation and AI to sustainable production practices, to refine your strategies.
      • Benchmark against competitors to identify growth opportunities, market gaps, and high-demand products.
    3. Supply Chain Optimization and Risk Mitigation

      • Connect with supply chain leaders and operational managers to optimize logistics, improve vendor relationships, and mitigate risks.
      • Present solutions for efficiency, cost savings, or enhanced supply chain transparency.
    4. Recruitment and Talent Development

      • Target HR professionals and hiring managers recruiting for roles in engineering, operations, or manufacturing management.
      • Provide staffing solutions, training platforms, or professional development tools tailored to the manufacturing industry.

    Why Choose Success.ai?

    1. Best Price Guarantee
      • Access premium-quality manufacturing data at competitive prices, ensuring strong ROI for your outreach, marketing, a...
  3. T

    Iron Ore - Price Data

    • tradingeconomics.com
    • it.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Dec 21, 2015
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    TRADING ECONOMICS (2015). Iron Ore - Price Data [Dataset]. https://tradingeconomics.com/commodity/iron-ore
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    excel, json, xml, csvAvailable download formats
    Dataset updated
    Dec 21, 2015
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Oct 22, 2010 - Aug 29, 2025
    Area covered
    World
    Description

    Iron Ore rose to 101.81 USD/T on August 29, 2025, up 0.10% from the previous day. Over the past month, Iron Ore's price has risen 2.77%, and is up 3.15% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Iron Ore - values, historical data, forecasts and news - updated on September of 2025.

  4. Material extraction (used) (construction minerals) from Global Material...

    • data.niaid.nih.gov
    Updated Mar 15, 2023
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    International Resource Panel (2023). Material extraction (used) (construction minerals) from Global Material Flows Database [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_7728248
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    Dataset updated
    Mar 15, 2023
    Dataset authored and provided by
    International Resource Panelhttps://www.resourcepanel.org/
    Description

    The following data was used in the paper "Schiller & Roscher (2023). Impact of Urbanization on construction material consumption: A global analysis" to calculate material consumption of non-metallic mineral construction materials.

    This dataset provided data on the extraction of mineral construction materials that are used for further processes. The data represent the extraction of raw materials from the environment by country. They are based on reported data on the one hand and estimated data on the other. The specific assumptions and factors for the estimates can be found in Krausmann et al. (2009). Growth in global material use, GDP and population during the 20th century. Ecological Economics 68(10) 2696-2705. doi: 10.1016/j.ecolecon.2009.05.007. In the MFA methodology, some categories of materials are defined as "unused extraction" because they are not economically used or further processed. For example, unused materials include overburden from mining activities and unused residues from biomass extraction (OECD, 2008). These are not included in presented data.

    The following materials belong to the group of construction minerals: asphalt, chert and flint, common clay, clay for bricks etc., crushed stone, igneous rock, lava sand, limestone, marl, shell, loam, marble, travertines, sand and gravel, sandstone, slate and turfaceous rock (see Lutter, S., Lieber, M., & Giljum, S. (2016). Global Materialflow database. Material extraction data. Technical Report, Version 2015.1. retrieved February 2018 from www.materialflows.net). The status of the given data is spring 2018 and was downloaded from www.materialflows.net at this time. Due to restructuring of the website, 2018 data is no longer available online. Current data on material extraction and consumption can be found on United Nations Environment Programme, International Resource Panel (IRP). (2023). Global Material Flows Database. https://www.resourcepanel.org/global-material-flows-database.

  5. Global Agricultural Raw Materials Imports by Country, 2023

    • reportlinker.com
    Updated Apr 9, 2024
    + more versions
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    ReportLinker (2024). Global Agricultural Raw Materials Imports by Country, 2023 [Dataset]. https://www.reportlinker.com/dataset/2d9beb74a7571326d8c73c7e9d1bff42402fdb1a
    Explore at:
    Dataset updated
    Apr 9, 2024
    Dataset authored and provided by
    ReportLinker
    License

    Attribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
    License information was derived automatically

    Description

    Global Agricultural Raw Materials Imports by Country, 2023 Discover more data with ReportLinker!

  6. d

    Data from: Global Value Chain and Manufacturing Analysis on Geothermal Power...

    • catalog.data.gov
    • gdr.openei.org
    • +4more
    Updated Jan 20, 2025
    + more versions
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    National Renewable Energy Laboratory (2025). Global Value Chain and Manufacturing Analysis on Geothermal Power Plant Turbines [Dataset]. https://catalog.data.gov/dataset/global-value-chain-and-manufacturing-analysis-on-geothermal-power-plant-turbines-373cd
    Explore at:
    Dataset updated
    Jan 20, 2025
    Dataset provided by
    National Renewable Energy Laboratory
    Description

    In this study, we have undertaken a robust analysis of the global supply chain and manufacturing costs for components of Organic Rankine Cycle (ORC) Turboexpander and steam turbines used in geothermal power plants. We collected a range of market data influencing manufacturing from various data sources and determined the main international manufacturers in the industry. The data includes the manufacturing cost model to identify requirements for equipment, facilities, raw materials, and labor. We analyzed three different cases; 1) 1 MW geothermal ORC Turboexpander 2) 5 MW ORC Turboexpander 3) 20 MW geothermal Steam Turbine

  7. v

    Global export data of Cosmetic Raw Material

    • volza.com
    csv
    Updated Jun 8, 2025
    + more versions
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    Volza FZ LLC (2025). Global export data of Cosmetic Raw Material [Dataset]. https://www.volza.com/p/cosmetic-raw-material/export/
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    csvAvailable download formats
    Dataset updated
    Jun 8, 2025
    Dataset authored and provided by
    Volza FZ LLC
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Variables measured
    Count of exporters, Sum of export value, 2014-01-01/2021-09-30, Count of export shipments
    Description

    24940 Global export shipment records of Cosmetic Raw Material with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

  8. T

    Aluminum - Price Data

    • tradingeconomics.com
    • ko.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Sep 1, 2025
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    TRADING ECONOMICS (2025). Aluminum - Price Data [Dataset]. https://tradingeconomics.com/commodity/aluminum
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    json, excel, csv, xmlAvailable download formats
    Dataset updated
    Sep 1, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Oct 10, 1989 - Sep 1, 2025
    Area covered
    World
    Description

    Aluminum fell to 2,617.40 USD/T on September 1, 2025, down 0.11% from the previous day. Over the past month, Aluminum's price has risen 2.06%, and is up 7.98% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Aluminum - values, historical data, forecasts and news - updated on September of 2025.

  9. Global import data of Raw Material

    • volza.com
    csv
    Updated Jul 16, 2025
    + more versions
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    Volza FZ LLC (2025). Global import data of Raw Material [Dataset]. https://www.volza.com/p/raw-material/import/import-in-india/
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    csvAvailable download formats
    Dataset updated
    Jul 16, 2025
    Dataset provided by
    Authors
    Volza FZ LLC
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Variables measured
    Count of importers, Sum of import value, 2014-01-01/2021-09-30, Count of import shipments
    Description

    8618 Global import shipment records of Raw Material with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

  10. T

    Nickel - Price Data

    • tradingeconomics.com
    • ru.tradingeconomics.com
    • +13more
    csv, excel, json, xml
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    TRADING ECONOMICS (2025). Nickel - Price Data [Dataset]. https://tradingeconomics.com/commodity/nickel
    Explore at:
    excel, xml, csv, jsonAvailable download formats
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jul 20, 1993 - Sep 1, 2025
    Area covered
    World
    Description

    Nickel rose to 15,475 USD/T on September 1, 2025, up 0.45% from the previous day. Over the past month, Nickel's price has risen 2.45%, but it is still 6.92% lower than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Nickel - values, historical data, forecasts and news - updated on September of 2025.

  11. k

    Imports Weight by Nature of Items

    • datasource.kapsarc.org
    Updated Jun 30, 2025
    + more versions
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    (2025). Imports Weight by Nature of Items [Dataset]. https://datasource.kapsarc.org/explore/dataset/imports-weight-by-nature-of-items/
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    Dataset updated
    Jun 30, 2025
    Description

    Explore the imports weight by nature of items dataset, featuring information on finished products, raw materials, and semi-finished products in the international trade report. Discover key insights on imports in Saudi Arabia.

    Imports, Finished Products, Raw Material, Semi-Finished Products, International Trade Report

    Saudi ArabiaFollow data.kapsarc.org for timely data to advance energy economics research..According to the foreign trade system, it means the weight of all goods and commodities imported and entering the country to cover local needs, on which all customs procedures followed in ending the import of a commodity are performedMethodology Link: https://www.stats.gov.sa/en/node/9779

  12. Z

    Open database on global coal and metal mine production

    • data.niaid.nih.gov
    • zenodo.org
    • +1more
    Updated Feb 14, 2023
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    Giljum, Stefan (2023). Open database on global coal and metal mine production [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_6325108
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    Dataset updated
    Feb 14, 2023
    Dataset provided by
    Lieber, Mirko
    Giljum, Stefan
    Maus, Victor
    Jasansky, Simon
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    See also the associated Data Descriptor published in Nature Scientific Data: www.nature.com/articles/s41597-023-01965-y

    This data set covers global extraction of coal and metal ores on an individual mine level. It covers 1171 individual mines in 80 different countries, reporting mine-level production for 80 different materials in the period 2000-2021. Furthermore, also data on mining coordinates, ownership, mineral reserves, mining waste, transportation of mining products, as well as mineral processing capacities (smelters and mineral refineries) and production is included. The data was gathered manually from more than 1900 openly available sources, such as annual or sustainability reports of mining companies. All datapoints are linked to their respective source documents. After manual screening and entry of the data, automatic cleaning, harmonization and data checking was conducted. Geoinformation was obtained either from coordinates available in company reports, or by retrieving the coordinates via Google Maps API and subsequent manual checking. For mines where no coordinates could be found, other geospatial attributes such as province, region, district or municipality were recorded, and linked to the GADM data set, available at www.gadm.org.

    The data set, found in the "data" sub-folder, consists of 12 tables. The table “facilities” contains descriptive and spatial information of mines and processing facilities, and is available as a GeoPackage (GPKG) file. All other tables are available in comma-separated values (CSV) format. If you are working in Excel or have problems handling the GeoPackage file, it can be converted to Excel with an online tool, such as https://mygeodata.cloud/converter/gpkg-to-xlsx.

    A schematic depiction of the database is provided in the file database_model.pdf. A description of all variables of all tables is provided in the Excel file variables_descriptions.xlsx, and all materials for which production is reported in the database are listed in the file materials_covered.xlsx.

    For convenience, global and national coverage shares for every material and country with recorded production in the database is provided in the file coverage_table.pdf. These coverage shares were calculated by comparing the production values of this database to official production statistics reported in the UNEP IRP Global Material Flows Database, to be found under https://www.resourcepanel.org/global-material-flows-database. For significant raw material producing countries, these coverage shares are also visualised in the file coverage_national_area_charts.pdf.

  13. m

    Data from: Compilation, Revision and Updating of the Global VAR (GVAR)...

    • data.mendeley.com
    Updated Jan 2, 2024
    + more versions
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    Kamiar Mohaddes (2024). Compilation, Revision and Updating of the Global VAR (GVAR) Database, 1979Q2-2023Q3 [Dataset]. http://doi.org/10.17632/kfp5fhgkvf.1
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    Dataset updated
    Jan 2, 2024
    Authors
    Kamiar Mohaddes
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This is the latest version of the Global VAR (GVAR) dataset - a global modelling framework for analyzing the international macroeconomic transmission of shocks while accounting for drivers of economic activity, interlinkages and spillovers between different countries, and the effects of unobserved or observed common factors. This dataset includes quarterly macroeconomic variables for 33 economies (log real GDP, y, the rate of inflation, dp, short-term interest rate, r, long-term interest rate, lr, the log deflated exchange rate, ep, and log real equity prices, eq, as well as quarterly data on commodity prices (oil prices, poil, agricultural raw material, pmat, and metals prices, pmetal), from 1979Q2 to 2023Q3. These 33 countries cover more than 90% of world GDP.

    It would be appreciated if use of the updated dataset could be acknowledged as: “Mohaddes, K. and M. Raissi (2024). Compilation, Revision and Updating of the Global VAR (GVAR) Database, 1979Q2-2023Q3. University of Cambridge: Judge Business School (mimeo)”.

    For more details on Global VAR (GVAR) modelling, see also www.mohaddes.org/gvar

  14. Import/Export Trade Data in Colombia

    • kaggle.com
    Updated Sep 10, 2024
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    Techsalerator (2024). Import/Export Trade Data in Colombia [Dataset]. https://www.kaggle.com/datasets/techsalerator/importexport-trade-data-in-colombia/discussion
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Sep 10, 2024
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Techsalerator
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Area covered
    Colombia
    Description

    Techsalerator’s Import/Export Trade Data for Colombia

    Techsalerator’s Import/Export Trade Data for Colombia offers a detailed and insightful collection of information on international trade activities involving Colombian companies. This dataset provides an in-depth examination of trade transactions, documenting and classifying imports and exports across various industries within Colombia.

    To obtain Techsalerator’s Import/Export Trade Data for Colombia, please reach out to info@techsalerator.com or visit https://www.techsalerator.com/contact-us with your specific requirements. Techsalerator will provide a customized quote based on your data needs, with delivery available within 24 hours. Ongoing access options can also be discussed.

    Techsalerator's Import/Export Trade Data for Colombia delivers a thorough analysis of trade activities, integrating data from customs reports, trade agreements, and shipping records. This comprehensive dataset helps businesses, investors, and trade analysts understand Colombia’s trade landscape in detail.

    Key Data Fields

    Company Name: Lists the companies involved in trade transactions. This information helps identify potential partners or competitors and track industry-specific trade patterns. Trade Volume: Details the quantity or value of goods traded, providing insights into the scale and economic impact of trade activities. Product Category: Specifies the types of goods traded, such as raw materials or finished products, aiding in understanding market demand and supply chain dynamics. Import/Export Country: Identifies the countries of origin or destination for traded goods, offering insights into regional trade relationships and market access. Transaction Date: Records the date of transactions, revealing seasonal trends and shifts in trade dynamics over time.

    Top Trade Trends in Colombia

    Trade Balance Dynamics: Colombia’s trade balance fluctuates with major partners such as the United States and China. Ongoing trade agreements and policy adjustments aim to address imbalances and enhance trade relations. U.S.-Colombia Trade Relations: The trade relationship with the United States remains central, influenced by agreements like the U.S.-Colombia Trade Promotion Agreement. This partnership shapes significant aspects of Colombia's trade policy and practices. Expansion of Trade Networks: Colombia is diversifying its trade partners and markets beyond traditional partners, reflecting a trend toward broader global trade engagement. Growth in Export Commodities: Colombia continues to see substantial trade in key export commodities, including coffee, oil, and flowers, which play a critical role in its export economy. Focus on Trade Agreements: Colombia is actively pursuing new trade agreements and strengthening existing ones to boost its trade sector and market access.

    Notable Companies in Colombian Trade Data

    Ecopetrol: The national oil company, involved in exporting and importing energy products, impacting Colombia's energy trade. Grupo Aval: A major financial conglomerate with interests in international trade, including financial services for trade transactions. Alpina: A leading dairy company, engaged in both importing raw materials and exporting dairy products, reflecting its significant role in Colombia’s trade dynamics. Bavaria: A major beverage company involved in importing raw materials and exporting beer, contributing to Colombia’s trade in the beverage sector. Cemex Colombia: A key player in the construction sector, facilitating the import and export of construction materials and products.

    Accessing Techsalerator’s Data

    To obtain Techsalerator’s Import/Export Trade Data for Colombia, please contact us at info@techsalerator.com with your requirements. We will provide a customized quote based on the number of data fields and records needed, with delivery available within 24 hours. Ongoing access options can also be discussed.

    Included Data Fields:

    Company Name Trade Volume Product Category Import/Export Country Transaction Date Shipping Details Customs Codes Trade Value

    For detailed insights into Colombia’s import and export activities and trends, Techsalerator’s dataset is an invaluable resource for staying informed and making strategic decisions.

  15. Indicator 8.4.2: Domestic material consumption per capita by type of raw...

    • sdgs.amerigeoss.org
    Updated Aug 18, 2020
    + more versions
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    UN DESA Statistics Division (2020). Indicator 8.4.2: Domestic material consumption per capita by type of raw material (tonnes) [Dataset]. https://sdgs.amerigeoss.org/datasets/undesa::indicator-8-4-2-domestic-material-consumption-per-capita-by-type-of-raw-material-tonnes-5/about
    Explore at:
    Dataset updated
    Aug 18, 2020
    Dataset provided by
    United Nations Department of Economic and Social Affairshttps://www.un.org/en/desa
    Authors
    UN DESA Statistics Division
    Area covered
    Description

    Series Name: Domestic material consumption per capita by type of raw material (tonnes)Series Code: EN_MAT_DOMCMPCRelease Version: 2020.Q2.G.03 This dataset is the part of the Global SDG Indicator Database compiled through the UN System in preparation for the Secretary-General's annual report on Progress towards the Sustainable Development Goals.Indicator 8.4.2: Domestic material consumption, domestic material consumption per capita, and domestic material consumption per GDPTarget 8.4: Improve progressively, through 2030, global resource efficiency in consumption and production and endeavour to decouple economic growth from environmental degradation, in accordance with the 10-Year Framework of Programmes on Sustainable Consumption and Production, with developed countries taking the leadGoal 8: Promote sustained, inclusive and sustainable economic growth, full and productive employment and decent work for allFor more information on the compilation methodology of this dataset, see https://unstats.un.org/sdgs/metadata/

  16. T

    Polypropylene - Price Data

    • tradingeconomics.com
    • tr.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Aug 29, 2025
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    TRADING ECONOMICS (2025). Polypropylene - Price Data [Dataset]. https://tradingeconomics.com/commodity/polypropylene
    Explore at:
    json, xml, csv, excelAvailable download formats
    Dataset updated
    Aug 29, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Feb 28, 2013 - Aug 29, 2025
    Area covered
    World
    Description

    Polypropylene fell to 6,941 CNY/T on August 29, 2025, down 0.26% from the previous day. Over the past month, Polypropylene's price has fallen 3.13%, and is down 8.60% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. This dataset includes a chart with historical data for Polypropylene.

  17. f

    Sustainable Sourcing of Global Agricultural Raw Materials: Assessing Gaps in...

    • plos.figshare.com
    • datasetcatalog.nlm.nih.gov
    docx
    Updated Jun 2, 2023
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    Nathaniel P. Springer; Kelly Garbach; Kathleen Guillozet; Van R. Haden; Prashant Hedao; Allan D. Hollander; Patrick R. Huber; Christina Ingersoll; Megan Langner; Genevieve Lipari; Yaser Mohammadi; Ruthie Musker; Marina Piatto; Courtney Riggle; Melissa Schweisguth; Emily Sin; Sara Snider; Nataša Vidic; Aubrey White; Sonja Brodt; James F. Quinn; Thomas P. Tomich (2023). Sustainable Sourcing of Global Agricultural Raw Materials: Assessing Gaps in Key Impact and Vulnerability Issues and Indicators [Dataset]. http://doi.org/10.1371/journal.pone.0128752
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    docxAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Nathaniel P. Springer; Kelly Garbach; Kathleen Guillozet; Van R. Haden; Prashant Hedao; Allan D. Hollander; Patrick R. Huber; Christina Ingersoll; Megan Langner; Genevieve Lipari; Yaser Mohammadi; Ruthie Musker; Marina Piatto; Courtney Riggle; Melissa Schweisguth; Emily Sin; Sara Snider; Nataša Vidic; Aubrey White; Sonja Brodt; James F. Quinn; Thomas P. Tomich
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Understanding how to source agricultural raw materials sustainably is challenging in today’s globalized food system given the variety of issues to be considered and the multitude of suggested indicators for representing these issues. Furthermore, stakeholders in the global food system both impact these issues and are themselves vulnerable to these issues, an important duality that is often implied but not explicitly described. The attention given to these issues and conceptual frameworks varies greatly—depending largely on the stakeholder perspective—as does the set of indicators developed to measure them. To better structure these complex relationships and assess any gaps, we collate a comprehensive list of sustainability issues and a database of sustainability indicators to represent them. To assure a breadth of inclusion, the issues are pulled from the following three perspectives: major global sustainability assessments, sustainability communications from global food companies, and conceptual frameworks of sustainable livelihoods from academic publications. These terms are integrated across perspectives using a common vocabulary, classified by their relevance to impacts and vulnerabilities, and categorized into groups by economic, environmental, physical, human, social, and political characteristics. These issues are then associated with over 2,000 sustainability indicators gathered from existing sources. A gap analysis is then performed to determine if particular issues and issue groups are over or underrepresented. This process results in 44 “integrated” issues—24 impact issues and 36 vulnerability issues —that are composed of 318 “component” issues. The gap analysis shows that although every integrated issue is mentioned at least 40% of the time across perspectives, no issue is mentioned more than 70% of the time. A few issues infrequently mentioned across perspectives also have relatively few indicators available to fully represent them. Issues in the impact framework generally have fewer gaps than those in the vulnerability framework.

  18. Facebook users worldwide 2017-2027

    • statista.com
    • es.statista.com
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    Stacy Jo Dixon, Facebook users worldwide 2017-2027 [Dataset]. https://www.statista.com/topics/1164/social-networks/
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    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Stacy Jo Dixon
    Description

    The global number of Facebook users was forecast to continuously increase between 2023 and 2027 by in total 391 million users (+14.36 percent). After the fourth consecutive increasing year, the Facebook user base is estimated to reach 3.1 billion users and therefore a new peak in 2027. Notably, the number of Facebook users was continuously increasing over the past years. User figures, shown here regarding the platform Facebook, have been estimated by taking into account company filings or press material, secondary research, app downloads and traffic data. They refer to the average monthly active users over the period and count multiple accounts by persons only once.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).

  19. a

    Indicator 8.4.1: Material footprint per unit of GDP by type of raw material...

    • sdgs.amerigeoss.org
    • unstats-undesa.opendata.arcgis.com
    Updated Aug 18, 2020
    + more versions
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    UN DESA Statistics Division (2020). Indicator 8.4.1: Material footprint per unit of GDP by type of raw material (kilograms per constant 2010 United States dollar) [Dataset]. https://sdgs.amerigeoss.org/datasets/d5c8b495bc234f459edfd3dd08120151
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    Dataset updated
    Aug 18, 2020
    Dataset authored and provided by
    UN DESA Statistics Division
    Area covered
    United States,
    Description

    Series Name: Material footprint per unit of GDP by type of raw material (kilograms per constant 2010 United States dollar)Series Code: EN_MAT_FTPRPGRelease Version: 2020.Q2.G.03 This dataset is the part of the Global SDG Indicator Database compiled through the UN System in preparation for the Secretary-General's annual report on Progress towards the Sustainable Development Goals.Indicator 8.4.1: Material footprint, material footprint per capita, and material footprint per GDPTarget 8.4: Improve progressively, through 2030, global resource efficiency in consumption and production and endeavour to decouple economic growth from environmental degradation, in accordance with the 10-Year Framework of Programmes on Sustainable Consumption and Production, with developed countries taking the leadGoal 8: Promote sustained, inclusive and sustainable economic growth, full and productive employment and decent work for allFor more information on the compilation methodology of this dataset, see https://unstats.un.org/sdgs/metadata/

  20. d

    Global database of cement production assets and upstream suppliers

    • datadryad.org
    • search.dataone.org
    zip
    Updated Oct 4, 2023
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    Nataliya Tkachenko; Kevin Tang; Matt McCarten; Steven Reece; David Kampmann; Conor Hickey; Maral Bayaraa; Peter Foster; Courtney Layman; Cristian Rossi; Kimberly Scott; David Yoken; Christophe Christiaen; Ben Caldecott (2023). Global database of cement production assets and upstream suppliers [Dataset]. http://doi.org/10.5061/dryad.6t1g1jx4f
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    zipAvailable download formats
    Dataset updated
    Oct 4, 2023
    Dataset provided by
    Dryad
    Authors
    Nataliya Tkachenko; Kevin Tang; Matt McCarten; Steven Reece; David Kampmann; Conor Hickey; Maral Bayaraa; Peter Foster; Courtney Layman; Cristian Rossi; Kimberly Scott; David Yoken; Christophe Christiaen; Ben Caldecott
    Time period covered
    Jul 15, 2023
    Description

    Global database of cement production assets and upstream suppliers

    https://doi.org/10.5061/dryad.6t1g1jx4f

    Description of the data

    This database has been created as part of the GeoAsset programme under the Spatial Finance Initiative (UK Centre for Greening Finance and Investment/University of Oxford) in collaboration with Astraea Inc. For more information about this work, visit https://www.cgfi.ac.uk/spatial-finance-initiative/geoasset-project/

    Suggested citation: Tkachenko, N., Tang, K., McCarten, M., Reece, S., Kampmann, D., Hickey, C., Bayaraa, M., Foster, P., Layman, C., Rossi, C., Scott, K., Yoken, D., Christiaen, C. and Caldecott, B. (2023) Global database of cement production assets and upstream suppliers [Dataset]. Dryad. https://doi.org/10.5061/dryad.6t1g1jx4f

    Please contact [nataliya.tkachenko@lloydsbanking.com...

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TRADING ECONOMICS, Steel - Price Data [Dataset]. https://tradingeconomics.com/commodity/steel

Steel - Price Data

Steel - Historical Dataset (2009-03-27/2025-09-02)

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75 scholarly articles cite this dataset (View in Google Scholar)
xml, csv, excel, jsonAvailable download formats
Dataset authored and provided by
TRADING ECONOMICS
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Time period covered
Mar 27, 2009 - Sep 2, 2025
Area covered
World
Description

Steel rose to 3,076 CNY/T on September 2, 2025, up 0.89% from the previous day. Over the past month, Steel's price has fallen 3.78%, but it is still 1.02% higher than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Steel - values, historical data, forecasts and news - updated on September of 2025.

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