Find Tables and Columns

The Exhaustive Column Referential is the source of truth for DataHawk schemas, tables, columns, data types, and field descriptions. This page shows you how to navigate that reference instead of relying on a static table catalog that can go stale.

Open the schema reference

Start from the Exhaustive Column Referential. The Sheet is designed for filtering, sorting, and searching across schemas, tables, columns, data types, and descriptions.

Each row represents a field in a table. The most useful columns are usually:

• Schema: Top-level grouping such as PRODUCT, FINANCE, ADVERTISING, or REPORTS
• Table: Table name within that schema
• Column: Field name as it appears in Snowflake or BigQuery
• Description: What the field represents
• Data type: Expected format for the field

Start from the business question

Before searching, translate the question into a data domain.

If you are not sure where to start, use Source Systems & Freshness to map data types to source systems and schemas.

Filter by schema or table

Use the Sheet's built-in filters to narrow the rows:

1. Filter Schema to the domain you identified.
2. Filter or search Table if you already know part of the table name.
3. Search Description for business terms such as buy box, refund, inventory, campaign, or search volume.

Filtering first makes search results less noisy, especially for common words like sales, date, or brand.

Search by concept or column name

If you know the business concept but not the column name, search the descriptions. If you know part of the field name, search the Column field directly.

Useful examples:

Check the table grain

Before building a query or dashboard, confirm what one row represents. This is the most common source of mismatched numbers.

Look for clues in the table name, key columns, date fields, and descriptions:

• Product tables may be one row per ASIN, parent ASIN, product key, or snapshot date.
• Advertising tables may be account-level, campaign-level, keyword-level, or product-level.
• Finance tables may be event-level, order-level, ledger-level, or daily aggregation.
• Report tables may already join multiple schemas and hide lower-level grain.

When a page exists for the dataset family, use it to confirm grain and caveats. For example:

Check date and freshness fields

Tables may include several date-like fields. Pick the one that matches your analysis:

For source-system delays and freshness guidance, see Source Systems & Freshness.

Watch for preview and deprecated tables

The schema reference may include tables marked as preview, experimental, deprecated, legacy, or aliases. Treat those labels as implementation guidance:

• Preview / experimental: Useful for exploration, but avoid production dashboards unless your DataHawk contact confirms stability.
• Deprecated / legacy: Migrate to the replacement table where documented.
• Alias: Still resolves today, but use the canonical table for new work.
• Raw: Closer to the source API, often more granular and less curated.

Examples

Find the table for Buy Box owner

1. Start with the PRODUCT schema because Buy Box is product-offer data.
2. Search for featured offer or buy box.
3. Look for AMZN_PRODUCT_FEATURED_OFFER and fields such as FEATURED_SELLER_ID.
4. Confirm field meaning in Product Data Reference.

Find sales estimate columns

1. Start with PRODUCT, MARKET, or REPORTS, depending on whether you need product-level, category-level, or curated report data.
2. Search for sales estimates, UNITS_CHILD, REVENUE_CHILD, or TRUST_INDEX.
3. Confirm current V7 tables and deprecated aliases in Sales Estimates Data.

Find advertising campaign metrics

1. Start with ADVERTISING.
2. Search for campaign, spend, sales, clicks, or sponsored_type.
3. Choose the table grain that matches the dashboard or query: account, campaign, keyword, product, or SKU.
4. For Walmart-specific tables, use Walmart Advertising Data.

Find currency conversion fields

1. Start with REFERENTIAL.
2. Search for currency or exchange rate.
3. Use REFERENTIAL_CURRENCY_RATE for daily exchange rates and REFERENTIAL_MARKETPLACE when you need the currency attached to a marketplace.
4. For a SQL example, see Convert Currencies.

Where to go next