We extract economic indicators, policy trackers, statistical databases, and publications from OECD Data Explorer. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Economic Indicators objects from oecd.org. All fields typed and schema-versioned.
"indicator_id": "DP_LIVE", "indicator_name": "Gross domestic product (GDP)", "subject": "TOT", "measure": "MLN_USD", "frequency": "A", "country_code": "GBR", "time_period": "2023", "value": 3421000.5
| # | indicator_id | indicator_name | subject | measure | frequency | country_code |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Publications & Reports objects from oecd.org. All fields typed and schema-versioned.
"publication_id": "9789264111111-en", "title": "OECD Economic Outlook", "authors": "['OECD']", "publication_date": "2023-11-29", "isbn": "9789264111111", "doi": "10.1787/12345678-en", "abstract": "Analysis of major economic trends.", "language": "English"
| # | publication_id | title | authors | publication_date | isbn | doi |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for PISA Education Data objects from oecd.org. All fields typed and schema-versioned.
"cycle_year": "2022", "country": "Japan", "math_score": 536, "reading_score": 516, "science_score": 547, "equity_index": 0.85, "student_count": 6500, "male_score": 540
| # | cycle_year | country | region | math_score | reading_score | science_score |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Tax Policy Data objects from oecd.org. All fields typed and schema-versioned.
"tax_domain": "Corporate Tax", "country": "FRA", "year": "2022", "tax_type": "Income and Profits", "revenue_value": 85000.0, "currency": "EUR", "percentage_gdp": 2.8, "statutory_rate": 25.8
| # | tax_domain | country | year | tax_type | revenue_value | currency |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Environmental Indicators objects from oecd.org. All fields typed and schema-versioned.
"indicator_type": "Air and Climate", "pollutant": "CO2", "country": "DEU", "year": "2022", "emission_volume": 650.5, "unit": "Million tonnes", "sector": "Energy", "trend_percentage": -2.4
| # | indicator_type | pollutant | country | year | emission_volume | unit |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our OECD scraper handles every layer of the platform: statistical databases, policy trackers, and publication metadata. We bypass complex frontend rendering to extract raw SDMX and JSON arrays.
Parse the modern OECD Data Explorer interface, extracting multi-dimensional datasets across all available filters and time periods.
Convert complex SDMX structures and pivot tables into flat, queryable time-series records suitable for immediate warehouse ingestion.
Extract titles, abstracts, DOIs, ISBNs, and author lists from the OECD iLibrary, including direct links to open-access PDF assets.
Compile unified datasets per member and non-member country, tracking GDP, inflation, and unemployment metrics in a single schema.
Extract historical statutory tax rates, revenue statistics, and corporate tax policy data across all 38 member states.
Extract granular education metrics, gender breakdowns, and regional performance scores from the Programme for International Student Assessment.
Monitor greenhouse gas emissions, renewable energy adoption, and policy stringency indices updated quarterly.
Bypass frontend rendering entirely where possible, hitting underlying SDMX endpoints for higher throughput and schema stability.
Run one-off bulk exports or configure continuous pipelines at monthly or quarterly cadences aligned with OECD release schedules.
Brief in. Clean data out.
Provide dataset URLs, indicator codes, or subject areas. We design the extraction schema together.
We configure SDMX parsers, API pagination logic, and rate-limit handling for oecd.org.
Schema validation, unit normalisation checks, and missing data detection before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
OECD data structures are notoriously complex. Here is how we operationalise them.
OECD datasets use deep multi-dimensional structures. We flatten these SDMX cubes into relational formats, unrolling dimensions like country, time, and measure into standard database columns.
The new OECD Data Explorer relies heavily on client-side state. We map the underlying API calls and session tokens to extract raw JSON rather than scraping the DOM.
Many OECD interfaces cap CSV exports at 1 million rows. We paginate programmatically through the backend APIs, extracting full historical datasets without truncation.
OECD frequently updates indicator codes and measurement units. Our pipeline detects schema drift, mapping legacy codes to current identifiers and alerting on unit changes.
While public, OECD infrastructure enforces strict rate limits. We distribute requests across our proxy pool and implement exponential backoff to ensure reliable, continuous extraction.
Quant funds and economists ingest historical GDP, CPI, and employment data to train macro models.
Think tanks and academia track tax policy shifts, environmental regulations, and healthcare spending across member states.
ESG analysts integrate OECD environmental indicators and social metrics into proprietary corporate scoring frameworks.
Fixed income teams monitor fiscal balances, debt-to-GDP ratios, and structural deficit metrics for sovereign bond pricing.
EdTech companies and policymakers analyse PISA scores to identify regional performance gaps and curriculum efficacy.
Procurement teams track trade balances, foreign direct investment, and production indices to assess geopolitical risk.
"The OECD publishes the definitive datasets for global macroeconomics and policy, but their multi-dimensional cubes require heavy engineering to flatten and operationalise."
Extracting data from the OECD Data Explorer involves handling complex SDMX formats, undocumented API pagination, and strict export limits. DataFlirt handles the extraction, normalisation, and delivery, so your quantitative analysts receive clean, flat time-series records ready for immediate modelling.
Everything supported by our oecd.org scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Custom parsers designed specifically for multi-dimensional statistical data. We bypass frontend rendering to query OECD's backend APIs directly for maximum throughput.
Pipelines run on Kubernetes clusters with intelligent rate-limit handling. We respect institutional infrastructure while maintaining strict delivery SLAs.
Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About oecd.org scraping, legality, and pipeline operations.
Ask us directly →Yes. OECD data is generally public domain or available under open licences intended for public use and dissemination. We strictly extract publicly accessible statistical data and publication metadata, adhering to their open data guidelines.
The Data Explorer uses complex client-side rendering. Rather than scraping the DOM, our pipeline reverse-engineers the underlying API requests, extracting the raw SDMX-JSON responses for higher accuracy and stability.
Yes. We configure pipelines to iterate through all standard country codes (both OECD members and tracked non-members), compiling unified time-series datasets.
We bypass frontend export limitations entirely by paginating through the backend APIs programmatically, allowing us to extract multi-million row datasets without truncation.
Yes. We extract all available frequencies for a given indicator, normalising the time-period formatting into standard ISO timestamps.
We extract comprehensive metadata (abstracts, authors, DOIs). We do not extract gated full-text PDFs that require institutional iLibrary subscriptions.
We align our extraction cadences with OECD's publication schedule. Pipelines can run daily, weekly, or monthly depending on the specific indicator's update frequency.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off historical export or continuous macro indicator feeds — we scope, build, and operate the pipeline. Tell us what you need.
