Snowflake

Data Availability

Clients using Snowflake have access to three core tables:

Companies: Company identifiers, metadata, and reference information
Series: Time-series financial data with period identifiers
Fundamentals: Core fundamental metrics and financial statement data

Snowflake vs. API Coverage

Capability	Snowflake	API
Companies	✓	✓
Series	✓	✓
Fundamentals	✓	✓
Download (company model)	—	✓
Export (CSV with series and datapoints)	—	✓
Industry Models	—	✓
Taxonomy (standardized metrics mapping)	✓	✓
Documents (download and keyword search)	—	✓

Future Data: Additional data sources will be added in future releases.

Important Details: Columns and fields for each table mirror our API responses with minor differences — clients familiar with our API will recognize the same structure.

Key Benefits

Zero Setup Time: Access data within 15 minutes of provisioning via the marketplace
No ETL Required: Data appears natively in your Snowflake account
Seamless Integration: Join Daloopa data with internal datasets without data movement
Scalable Access: Multiple teams can query without hitting API rate limits
Instant Updates: Data refreshes reflect immediately in your environment
Enterprise Security: Native Snowflake role-based access control

How It Works

Daloopa distributes data via a private listing on the Snowflake Marketplace. Once access is provisioned, you subscribe to the listing and can access data instantly in your Snowflake environment.

Schemas

Companies — One row per company. Master list of all companies with available Daloopa datasheets:

Column	Type	Description
id	BIGINT	Unique identifier for the company in Daloopa
name	STRING	Legal name of the company (e.g., "Apple Inc.")
ticker	STRING	Ticker symbol of the company
industry	STRING	Industry classification (e.g., "Technology Hardware, Storage & Peripherals")
sector	STRING	Sector classification (e.g., "Information Technology")
company_identifiers	VARIANT	Company identifiers (e.g., ISIN, CIK, CapIQCompanyId). ISIN is recommended as the primary match key (stored with `I_` prefix, e.g. `I_US0378331005`)
model_updated_at	TIMESTAMP	Timestamp when the company's Daloopa model was last updated
earliest_quarter	STRING	First period with available data for the company (e.g., "2015Q1")
latest_quarter	STRING	Latest period with available data for the company (e.g., "2025Q1")

Series — One row per series per company. A series represents a distinct financial line item tracked over time:

Column	Type	Description
id	BIGINT	Unique identifier for the series
company_id	BIGINT	Foreign key to `Companies.id`
full_series_name	STRING	Full hierarchical context of the series within the Daloopa model (e.g., "Income Statement \| Total cost of sales"). Pipe-delimited path from section to line item

Fundamentals — One row per datapoint. Each row is a single reported value (one series, one period, one filing):

Column	Type	Description
id	BIGINT	Unique identifier for the datapoint
company_id	BIGINT	Foreign key to `Companies.id`
series_id	BIGINT	Foreign key to `Series.id`
label	STRING	Short description of the datapoint (e.g., "iPhone", "Total Revenue")
category	STRING	Section or grouping under which the datapoint is categorized in the model (e.g., "Income Statement", "Balance Sheet", "Cash Flow Statement", "KPIs", "Segmental Breakdown", "Guidance")
title	STRING	Full hierarchical context of the datapoint within the Daloopa datasheet (e.g., "KPIs \| Customer Development \| Internet Users \| Technology Companies")
restated	BOOLEAN	Whether the datapoint has been restated in a subsequent filing (`true` = this value was revised from its original report)
filing_type	STRING	Type of regulatory filing from which the datapoint was sourced (e.g., "8-K", "10-Q", "10-K")
value_raw	DECIMAL(38,9)	Raw value of the datapoint as reported in the source filing
value_normalized	DECIMAL(38,9)	Normalized value, adjusted for consistency (e.g., annualized quarterly values converted to a comparable basis)
unit	STRING	Unit of measurement (e.g., "Billion", "Million", "Dollar", "Percent")
calendar_period	STRING	Calendar period, formatted as `YYYYQ#` for quarters or `YYYYFY` for fiscal years (e.g., "2021Q2", "2020FY"). Determined by the midpoint of the fiscal period falling within a calendar quarter
fiscal_period	STRING	Company's actual fiscal period, formatted as `YYYYQ#` or `YYYYFY` (e.g., "2024Q1"). May differ from `calendar_period` for companies with non-standard fiscal year ends
span	STRING	Periodicity of the datapoint (e.g., "Quarterly", "Annual")
fiscal_date	DATE	End date of the fiscal period for the datapoint (e.g., 2023-12-31)
document_id	BIGINT	Unique identifier for the source document (filing) from which the datapoint was extracted
filing_date	DATE	Date the regulatory filing was reported
document_released_at	TIMESTAMP	Datetime when the source document was ingested into Daloopa (i.e., when the datapoint became available)
created_at	TIMESTAMP	Timestamp when the datapoint was originally created in Daloopa
updated_at	TIMESTAMP	Timestamp of the last modification to the datapoint
is_incremental_update	BOOLEAN	Whether this datapoint is from an incremental (real-time) update that has not yet been incorporated into the published datasheet

Taxonomy Metrics — Standardized metric definitions that enable cross-company comparisons:

Column	Type	Description
id	BIGINT	Unique identifier for the taxonomy metric
name	STRING	Human-readable name of the metric (e.g., "Revenue", "Net Income")
description	STRING	Description of what the metric represents
global_metric	BOOLEAN	Whether this is a global metric that all companies should have (`true` = universal metric like Revenue)
fallback_metric_id	BIGINT	Foreign key to `Taxonomy Metrics.id`. Alternative metric to use if this metric is unavailable for a company

Taxonomy Metric Series — Junction table mapping taxonomy metrics to company-specific series:

Column	Type	Description
metric_id	BIGINT	Foreign key to `Taxonomy Metrics.id`
series_id	BIGINT	Foreign key to `Series.id`

Taxonomy Sub-Industries — Industry classification hierarchy:

Column	Type	Description
id	BIGINT	Unique identifier for the sub-industry
name	STRING	Display name of the sub-industry (e.g., "Software Publishers"). Most granular level of the classification hierarchy
industry_name	STRING	Parent industry name (e.g., "Software")
sub_sector_name	STRING	Parent sub-sector name
sector_name	STRING	Top-level sector name (e.g., "Information Technology")

Taxonomy Sub-Industry Companies — Junction table mapping companies to their sub-industry classification:

Column	Type	Description
sub_industry_id	BIGINT	Foreign key to `Taxonomy Sub-Industries.id`
company_id	BIGINT	Foreign key to `Companies.id`

Getting Started

1. Create Database from Listing

Install the Daloopa listing from the Snowflake Marketplace and create a database from it.

2. Access Data

-- Query the companies table (fully available)
SELECT * FROM <database_name>.SHARED.COMPANIES ORDER BY ID ASC;

-- Query restricted tables (only shows data for subscribed companies)
SELECT * FROM <database_name>.SHARED.SERIES;

SELECT * FROM <database_name>.SHARED.FUNDAMENTALS WHERE IS_INCREMENTAL_UPDATE;

The COMPANIES table is fully available, allowing you to browse all companies and decide which ones to subscribe to. The SERIES and FUNDAMENTALS tables are restricted and only return data for companies you are subscribed to. The FUNDAMENTALS table is further restricted — only users with a Daloopa Plus subscription are able to see fundamentals that are incremental.

3. Subscribe to Companies

To access data in SERIES and FUNDAMENTALS for a specific company, subscribe using the following endpoint with an API key:

Endpoint: POST https://app.daloopa.com/api/v2/snowflake/company-subscription

Request Body:

{
  "company_id": <company_id>
}