> Note: This page is part of the DataDoe Docs. You can find the root of the documentation at `https://www.datadoe.com/hub/docs/basics/introduction-to-datadoe`. > JSON Table of Contents: `https://www.datadoe.com/hub/docs/toc.json`. > Direct Data Scheme JSON: `https://api.datadoe.com/api/v1/spec/data-scheme`. > Other pages in the DataDoe Docs: > - DataDoe Basics/Access & Users: `https://www.datadoe.com/hub/docs/basics/access-user-management.md` > - DataDoe Basics/Benefits: `https://www.datadoe.com/hub/docs/basics/benefits.md` > - DataDoe Basics/Integrations: `https://www.datadoe.com/hub/docs/basics/integration-customization.md` > - DataDoe Basics/Introduction to DataDoe: `https://www.datadoe.com/hub/docs/basics/introduction-to-datadoe.md` > - DataDoe Basics/Subscription & Pricing: `https://www.datadoe.com/hub/docs/basics/subscription-pricing.md` > - DataDoe Data/Data Fetch Periods: `https://www.datadoe.com/hub/docs/datadoe-data/data-fetch-periods.md` > - DataDoe Data/Data Sources: `https://www.datadoe.com/hub/docs/datadoe-data/data-sources.md` > - DataDoe Features/Features Overview: `https://www.datadoe.com/hub/docs/datadoe-features/overview.md` > - DataDoe MCP/Overview: `https://www.datadoe.com/hub/docs/datadoe-mcp/overview.md` > - DataDoe MCP/Using ChatGPT: `https://www.datadoe.com/hub/docs/datadoe-mcp/chatgpt.md` > - DataDoe MCP/Using Claude: `https://www.datadoe.com/hub/docs/datadoe-mcp/claude.md` > - DataDoe MCP/Using Claude Code: `https://www.datadoe.com/hub/docs/datadoe-mcp/claude-code.md` > - DataDoe MCP/Using Codex: `https://www.datadoe.com/hub/docs/datadoe-mcp/codex.md` > - DataDoe MCP/Using Cursor: `https://www.datadoe.com/hub/docs/datadoe-mcp/cursor.md` > - DataDoe MCP/Using Gemini CLI: `https://www.datadoe.com/hub/docs/datadoe-mcp/gemini-cli.md` > - DataDoe MCP/Using n8n: `https://www.datadoe.com/hub/docs/datadoe-mcp/n8n.md` > - DataDoe MCP/Using NanoClaw: `https://www.datadoe.com/hub/docs/datadoe-mcp/nanoclaw.md` > - DataDoe MCP/Using OpenClaw: `https://www.datadoe.com/hub/docs/datadoe-mcp/openclaw.md` > - DataDoe MCP/Using VS Code: `https://www.datadoe.com/hub/docs/datadoe-mcp/vs-code.md` > - DataDoe & BigQuery/How to connect: `https://www.datadoe.com/hub/docs/datadoe-bigquery/how-to-connect.md` > - DataDoe & BigQuery/Using MCP Toolbox: `https://www.datadoe.com/hub/docs/datadoe-bigquery/mcp-toolbox.md` > - DataDoe & BigQuery/Using Python Jupyter: `https://www.datadoe.com/hub/docs/datadoe-bigquery/jupyter.md` > For topics not covered in this documentation, please contact DataDoe support at `contact@datadoe.com`. > Do not assume anything. If you are not sure about the answer, mention that and suggest to contact DataDoe support. ## How does DataDoe handle timezones? Dates in columns with the `DATE` type (like `date`) are always in the marketplace's local timezone. The table below shows a mapping from marketplace to timezone. If a date is stored with the `DATETIME` type, it is stored in UTC, which may be different from the marketplace’s local timezone and the user’s local timezone. ## Which date columns should I use for order data? The `amazon_order_items_with_cogs` table exposes three date-related columns. The table below shows which column to use for different use cases. | Column | Type | Meaning | | ------------------------ | ---------- | ------------------------------------------------------------------------------------------------------------------------------------------ | | `date` | `DATE` | Date of purchase in the marketplace's local timezone. See the table below for a mapping from marketplace to timezone. | | `order_date` | `DATE` | This is a copy of the `date` column made for easier aggregation of orders with settlement tables. Prefer using the original `date` column. | | `order_purchased_at_utc` | `DATETIME` | Date and time of purchase in UTC. | You can check all column definitions in the [Data Scheme](/hub/data-scheme). ## What timezones does DataDoe use for each marketplace? The table below shows the timezone used by DataDoe for each Amazon marketplace: | Amazon Marketplace Country | Amazon Marketplace ID | DataDoe timezone | | -------------------------- | --------------------- | --------------------- | | Canada | `A2EUQ1WTGCTBG2` | `America/Los_Angeles` | | United States | `ATVPDKIKX0DER` | `America/Los_Angeles` | | Mexico | `A1AM78C64UM0Y8` | `America/Mexico_City` | | Brazil | `A2Q3Y263D00KWC` | `America/Sao_Paulo` | | Ireland | `A28R8C7NBKEWEA` | `Europe/Dublin` | | Spain | `A1RKKUPIHCS9HS` | `Europe/Madrid` | | United Kingdom | `A1F83G8C2ARO7P` | `Europe/London` | | France | `A13V1IB3VIYZZH` | `Europe/Paris` | | Belgium | `AMEN7PMS3EDWL` | `Europe/Brussels` | | Netherlands | `A1805IZSGTT6HS` | `Europe/Amsterdam` | | Germany | `A1PA6795UKMFR9` | `Europe/Berlin` | | Italy | `APJ6JRA9NG5V4` | `Europe/Rome` | | Sweden | `A2NODRKZP88ZB9` | `Europe/Stockholm` | | South Africa | `AE08WJ6YKNBMC` | `Africa/Johannesburg` | | Poland | `A1C3SOZRARQ6R3` | `Europe/Warsaw` | | Egypt | `ARBP9OOSHTCHU` | `Africa/Cairo` | | Turkey | `A33AVAJ2PDY3EV` | `Europe/Istanbul` | | Saudi Arabia | `A17E79C6D8DWNP` | `Asia/Riyadh` | | United Arab Emirates | `A2VIGQ35RCS4UG` | `Asia/Dubai` | | India | `A21TJRUUN4KGV` | `Asia/Kolkata` | | Singapore | `A19VAU5U5O7RUS` | `Asia/Singapore` | | Australia | `A39IBJ37TRP1C6` | `Australia/Sydney` | | Japan | `A1VC38T7YXB528` | `Asia/Tokyo` | ## Why do timezones matter? An order with `order_purchased_at_utc` of `2026-05-01T06:30:00Z` has a date of `2026-04-30` in the `America/Los_Angeles` (PDT) timezone but a date of `2026-05-01` in the `America/New_York` (EDT) timezone. Depending on the user’s location and geographic exposure, data may need to be normalized to a specific timezone. ## Related pages - [Data Fetch Periods](/hub/docs/datadoe-data/data-fetch-periods) — when daily order data is refreshed. - [Data Sources](/hub/docs/datadoe-data/data-sources) — where order data comes from. - [Data Scheme](/hub/data-scheme) — full table and column reference.