{
  "title": "Big Data for Macroeconomic Statistics (BDMS)",
  "sourceUrl": "https://www.imf.org/en/capacity-development/training/icdtc/courses/bdms",
  "canonical": "https://www.imf.org/en/capacity-development/training/icdtc/courses/bdms",
  "overlayPath": "/en/capacity-development/training/icdtc/courses/bdms/index.md",
  "summary": "The workshop is delivered by data scientists of the IMF Big Data Center through lectures and hands-on workshops covering various Big Data applications pertinent to macroeconomic statistics, offering insights from both producer and user standpoints.",
  "publishDate": "2025-07-26",
  "sections": [
    {
      "heading": "Overview",
      "content": "- Workshop aimed at country officials from national statistics offices (NSOs) and central banks to acquire knowledge and skills to leverage Big Data and advanced technologies for generating high-frequency and detailed statistics to enhance macroeconomic monitoring and research in the region.\n- Delivered by data scientists of the IMF Big Data Center through lectures and hands-on workshops.\n- Offers insights from both producer and user standpoints.\n- Participants present and discuss use cases, engage in discussions, and benefit from shared insights and experiences.\n- Topic: Macroeconomic Statistics"
    },
    {
      "heading": "Target audience",
      "content": "- Technical staff and managers from national statistics offices and central banks involved in macroeconomic statistics, nowcasting, and data science projects.\n- Suitable for economists, statisticians, data scientists, and decision-makers overseeing related projects or teams."
    },
    {
      "heading": "Course objectives",
      "content": "Upon completion, participants should be able to:\n- Provide support in setting up Big Data architecture, encompassing data extraction, preprocessing, and visualization in their various organizations.\n- Demonstrate a practical knowledge of machine learning modeling, variable selection, performance analysis as well as model selection, for GDP nowcasting and trade monitoring (based on the IMF's PortWatch platform).\n- Demonstrate practical skills in the use of Google Earth Engine (GEE), Dynamic World, Jupyter Notebook and other geospatial and data science packages to analyze satellite data and generate high-frequency macroeconomic statistics.\n- Carry out textual analysis with natural language processing (NLP) technologies to support macroeconomic analysis.\n- Demonstrate the application of these Big Data technologies and resources to improve timelines and granularity of their official statistics.\n- Facilitate peer-learning on Big Data applications and explore collaborations between agencies working on projects of mutual interest.\n- Gain insights into setting up effective data science teams and developing institutional Big Data strategies to support innovation for macroeconomic statistics."
    },
    {
      "heading": "Delivery and core topics",
      "content": "- Combination of lectures and hands-on workshops led by IMF Big Data Center data scientists.\n- Practical applications relevant to macroeconomic statistics, including GDP nowcasting and trade monitoring via the IMF's PortWatch platform.\n- Geospatial analysis using Google Earth Engine (GEE), Dynamic World, and Jupyter Notebook.\n- Textual analysis using natural language processing (NLP).\n- Emphasis on both technical implementation (data extraction, preprocessing, visualization) and institutional practices (team setup, strategy development)."
    },
    {
      "heading": "Expected competencies and institutional outcomes",
      "content": "- Ability to set up and support organizational Big Data architectures for macroeconomic statistics.\n- Practical machine learning and model evaluation skills applicable to nowcasting and monitoring.\n- Capability to produce high-frequency, geospatially informed macroeconomic indicators from satellite data.\n- Competence in NLP-based textual analysis to enrich macroeconomic monitoring and research.\n- Strengthened inter-agency collaboration and peer-learning on Big Data projects.\n- Foundations for institutional Big Data strategies and effective data science teams to support innovation in official statistics."
    }
  ],
  "bullets": [
    "Workshop aimed at country officials from national statistics offices (NSOs) and central banks to acquire knowledge and skills to leverage Big Data and advanced technologies for generating high-frequency and detailed statistics to enhance macroeconomic monitoring and research in the region.",
    "Delivered by data scientists of the IMF Big Data Center through lectures and hands-on workshops.",
    "Offers insights from both producer and user standpoints.",
    "Participants present and discuss use cases, engage in discussions, and benefit from shared insights and experiences.",
    "Topic: Macroeconomic Statistics",
    "Technical staff and managers from national statistics offices and central banks involved in macroeconomic statistics, nowcasting, and data science projects.",
    "Suitable for economists, statisticians, data scientists, and decision-makers overseeing related projects or teams.",
    "Provide support in setting up Big Data architecture, encompassing data extraction, preprocessing, and visualization in their various organizations.",
    "Demonstrate a practical knowledge of machine learning modeling, variable selection, performance analysis as well as model selection, for GDP nowcasting and trade monitoring (based on the IMF's PortWatch platform).",
    "Demonstrate practical skills in the use of Google Earth Engine (GEE), Dynamic World, Jupyter Notebook and other geospatial and data science packages to analyze satellite data and generate high-frequency macroeconomic statistics.",
    "Carry out textual analysis with natural language processing (NLP) technologies to support macroeconomic analysis.",
    "Demonstrate the application of these Big Data technologies and resources to improve timelines and granularity of their official statistics.",
    "Facilitate peer-learning on Big Data applications and explore collaborations between agencies working on projects of mutual interest.",
    "Gain insights into setting up effective data science teams and developing institutional Big Data strategies to support innovation for macroeconomic statistics.",
    "Combination of lectures and hands-on workshops led by IMF Big Data Center data scientists.",
    "Practical applications relevant to macroeconomic statistics, including GDP nowcasting and trade monitoring via the IMF's PortWatch platform.",
    "Geospatial analysis using Google Earth Engine (GEE), Dynamic World, and Jupyter Notebook.",
    "Textual analysis using natural language processing (NLP).",
    "Emphasis on both technical implementation (data extraction, preprocessing, visualization) and institutional practices (team setup, strategy development).",
    "Ability to set up and support organizational Big Data architectures for macroeconomic statistics.",
    "Practical machine learning and model evaluation skills applicable to nowcasting and monitoring.",
    "Capability to produce high-frequency, geospatially informed macroeconomic indicators from satellite data.",
    "Competence in NLP-based textual analysis to enrich macroeconomic monitoring and research.",
    "Strengthened inter-agency collaboration and peer-learning on Big Data projects.",
    "Foundations for institutional Big Data strategies and effective data science teams to support innovation in official statistics."
  ],
  "alternates": {
    "markdown": "/en/capacity-development/training/icdtc/courses/bdms/index.md",
    "json": "/en/capacity-development/training/icdtc/courses/bdms/index.json",
    "bundleManifest": "/en/capacity-development/training/icdtc/courses/bdms/bundle-manifest.json"
  },
  "generatedAtUtc": "2026-09-29T16:33:41.866Z"
}