Brunei vs Comoros: Statistical performance indicators (SPI): Pillar 5 data infrastructure
Statistical performance indicators (SPI): Pillar 5 data infrastructure over time
- Brunei
- Comoros
How they compare
Brunei currently reports 40 scale 0-100 against 40 scale 0-100 in Comoros, a difference of 0 scale 0-100.
The two have swapped places 1 time across 9 shared years of data; in 2016 it was Brunei ahead.
Brunei ranks 160th and Comoros ranks 160th of 190 countries.
Brunei has averaged higher in every one of the 2 decades both report.
Head to head by decade
| Decade | Brunei | Comoros | Difference | Ahead |
|---|---|---|---|---|
| 2010s | 37.5 scale 0-100 | 23.75 scale 0-100 | 13.75 scale 0-100 | Brunei |
| 2020s | 47 scale 0-100 | 38 scale 0-100 | 9 scale 0-100 | Brunei |
Averages of every year both report within each decade.
Frequently asked questions
- Which has higher statistical performance indicators (spi): pillar 5 data infrastructure, Brunei or Comoros?
- Brunei, at 40 scale 0-100 against 40 scale 0-100 in Comoros as of 2024.
- What is the difference in statistical performance indicators (spi): pillar 5 data infrastructure between Brunei and Comoros?
- 0 scale 0-100, with Brunei ahead.
- How many years of comparable data are there for Brunei and Comoros?
- 9 years are reported by both, from 2016 to 2024.
- How do Brunei and Comoros rank globally for statistical performance indicators (spi): pillar 5 data infrastructure?
- Brunei ranks 160th and Comoros ranks 160th of 190 countries.
- Where does this data come from?
- Statistical Performance Indicators, World Bank (WB), published as Statistical performance indicators (SPI): Pillar 5 data infrastructure score (scale 0-100). Statizoid refreshes it automatically from the source and publishes the full history for both places.
Individual pages
About this data
The data infrastructure pillar overall score measures the hard and soft infrastructure segments, itemizing essential cross cutting requirements for an effective statistical system. The segments are: (i) legislation and governance covering the existence of laws and a functioning institutional framework for the statistical system; (ii) standards and methods addressing compliance with recognized frameworks and concepts; (iii) skills including level of skills within the statistical system and among users (statistical literacy); (iv) partnerships reflecting the need for the statistical system to be inclusive and coherent; and (v) finance mobilized both domestically and from donors.