Browse by Topic
Each topic groups data sources by the kind of data they publish. Click a topic to filter the source index, or explore the notes below to understand what to expect when ingesting each category.
Economics
Macro and micro economic indicators — GDP, inflation, output gaps, business cycles
Browse sources →Finance
Monetary, banking, and capital-markets data — interest rates, exchange rates, asset prices
Browse sources →Labor
Employment, wages, and workforce data — unemployment rates, job openings, earnings
Browse sources →Trade
International goods and services flows — exports, imports, tariffs, balance of payments
Browse sources →Agriculture
Crop production, food prices, agricultural trade, and land-use statistics
Browse sources →Energy
Fuel production, consumption, prices, and renewable capacity data
Browse sources →Environmental
Emissions, climate, biodiversity, and sustainability metrics
Browse sources →Population
Demographic data — population counts, age structures, migration, birth/death rates
Browse sources →Global
Cross-country or worldwide datasets spanning multiple regions
Browse sources →Aggregator
Canada
Development
Market data
Uk
Ingestion notes by topic
Common patterns and gotchas when building ETL pipelines for each data category.
Macro and micro economic indicators — GDP, inflation, output gaps, business cycles
Pipeline note
Most sources publish annual revisions; build your pipeline to handle back-fills and vintage data.
Monetary, banking, and capital-markets data — interest rates, exchange rates, asset prices
Pipeline note
High-frequency sources (daily/intraday); expect schema drift and API rate limits.
Employment, wages, and workforce data — unemployment rates, job openings, earnings
Pipeline note
Monthly releases with seasonal adjustment flags; store both seasonally adjusted and raw series.
International goods and services flows — exports, imports, tariffs, balance of payments
Pipeline note
HS code taxonomies change every 5 years; version your commodity dimension table carefully.
Crop production, food prices, agricultural trade, and land-use statistics
Pipeline note
Seasonal reporting cadence; crop years don't align with calendar years — normalise your time dimension.
Fuel production, consumption, prices, and renewable capacity data
Pipeline note
Multiple unit systems (MMBTU, MWh, barrels); standardise to a single energy unit in your model layer.
Emissions, climate, biodiversity, and sustainability metrics
Pipeline note
Long historical series with frequent revisions; IPCC methodology changes can break year-over-year comparisons.
Demographic data — population counts, age structures, migration, birth/death rates
Pipeline note
Census vintages vs. intercensal estimates differ; track the source estimate type in a metadata column.
Cross-country or worldwide datasets spanning multiple regions
Pipeline note
Country codes vary (ISO 3166, M49, FIPS); map to a canonical geography dimension on ingestion.