## Big Data for Macroeconomic Statistics

## Source details

**Canonical URL:** [Big Data for Macroeconomic Statistics](https://www.imf.org/en/capacity-development/training/icdtc/schedule/at/2026/bdmsat26-27)

## Other formats

- [Markdown version](/en/capacity-development/training/icdtc/schedule/at/2026/bdmsat26-27/index.md)
- [Structured JSON version](/en/capacity-development/training/icdtc/schedule/at/2026/bdmsat26-27/index.json)
- [Bundle manifest](/en/capacity-development/training/icdtc/schedule/at/2026/bdmsat26-27/bundle-manifest.json)

## Bibliographic details
- Session: AT 26.27
- Location: Ebene, Mauritius
- Dates: October 26-30, 2026 (1 week)
- Delivery method: In-person Training
- Primary language: English
- Interpretation language: French Portuguese
- Status: Deadline passed

---

### Overview and logistics
- Session No.: AT 26.27
- Location: Ebene, Mauritius
- Date: October 26-30, 2026 (1 week)
- Delivery Method: In-person Training
- Primary Language: English
- Interpretation Language: French Portuguese
- Deadline: Deadline passed

### Target audience and qualifications
- Intended participants:
  - Technical staff and managers from national statistics offices and central banks involved in macroeconomic statistics, nowcasting, and data science projects.
  - Economists, statisticians, data scientists, and decision-makers overseeing related projects or teams.
- Qualifications:
  - Expected to have a degree in economics, statistics, data science or equivalent experience.
  - Working knowledge of advanced programming languages such as Python and R is strongly recommended.

### Course description
- Audience: Country officials from national statistics offices (NSOs) and central banks seeking skills to leverage Big Data and advanced technologies for high-frequency and detailed statistics.
- Delivery: Lectures and hands-on workshops delivered by data scientists of the IMF Big Data Center.
- Emphases:
  - Big Data applications pertinent to macroeconomic statistics from both producer and user standpoints.
  - Participant presentations and discussion of use cases, peer learning, and experience sharing.

### Course objectives and learning outcomes
- Technical architecture and workflows:
  - Provide support in setting up Big Data architecture, encompassing data extraction, preprocessing, and visualization in their various organizations.
- Machine learning and nowcasting:
  - 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).
- Geospatial analysis:
  - 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.
- Textual analysis and NLP:
  - Carry out textual analysis with natural language processing (NLP) technologies to support macroeconomic analysis.
- Statistical production improvements:
  - Demonstrate the application of these Big Data technologies and resources to improve timelines and granularity of their official statistics.
- Institutional capacity and collaboration:
  - 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.

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## References

- [In-person Training](https://www.imf.org/en/capacity-development/training/icdtc/delivery-methods)
- [Core Elements of Banking Supervision (CBS)](https://www.imf.org/en/capacity-development/training/icdtc/schedule/at/2027/cbsat27-10)
- [Advanced Government Finance Statistics (GFS-A)](https://www.imf.org/en/capacity-development/training/icdtc/schedule/ce/2026/gfs-ace26-45)
- [Fiscal Sustainability (FS)](https://www.imf.org/en/capacity-development/training/icdtc/schedule/ce/2026/fsce26-38)
- [Safeguards Assessments of Central Banks (SAC)](https://www.imf.org/en/capacity-development/training/icdtc/schedule/at/2026/sacat26-30)
- [Macroeconomic Management in Resource Rich Countries (MRC)](https://www.imf.org/en/capacity-development/training/icdtc/schedule/ce/2026/mrcce26-44)

_Source: https://www.imf.org/en/capacity-development/training/icdtc/schedule/at/2026/bdmsat26-27_