DATA STORAGE CORPORATION: cost of revenue

What this measure means

Costs attributed to goods produced and sold and services provided during the period. This is not the sum of every operating expense.

Exact concept: us-gaap:CostOfRevenue. Each value covers an annual-duration reporting interval, shown with both start and end dates. Different units remain separate; no currency conversion or interpolation is applied.

Coverage of this history

Selected reporting periods run from 2010-01-01 to 2025-12-31. The SEC response was captured on 2026-09-20.

Selected filing history

Related financial histories

• DATA STORAGE CORPORATION: total assets
• DATA STORAGE CORPORATION: total liabilities
• DATA STORAGE CORPORATION: stockholders equity
• DATA STORAGE CORPORATION: cash and cash equivalents
• DATA STORAGE CORPORATION: net income or loss
• DATA STORAGE CORPORATION: operating cash flow
• DATA STORAGE CORPORATION: capital expenditure payments
• DATA STORAGE CORPORATION: revenue
• DATA STORAGE CORPORATION: financing cash flow
• DATA STORAGE CORPORATION: investing cash flow
• DATA STORAGE CORPORATION: retained earnings or deficit
• DATA STORAGE CORPORATION: basic weighted-average shares
• DATA STORAGE CORPORATION: diluted weighted-average shares
• DATA STORAGE CORPORATION: basic earnings per share
• DATA STORAGE CORPORATION: diluted earnings per share
• DATA STORAGE CORPORATION: income tax expense or benefit
• DATA STORAGE CORPORATION: net property, plant and equipment
• DATA STORAGE CORPORATION: share-based compensation expense
• DATA STORAGE CORPORATION: operating income or loss
• DATA STORAGE CORPORATION: current assets
• DATA STORAGE CORPORATION: interest expense
• DATA STORAGE CORPORATION: current liabilities
• DATA STORAGE CORPORATION: goodwill carrying amount
• DATA STORAGE CORPORATION: net finite-lived intangible assets
• DATA STORAGE CORPORATION: net current accounts receivable
• DATA STORAGE CORPORATION: operating expenses
• DATA STORAGE CORPORATION: gross profit
• DATA STORAGE CORPORATION: selling, general and administrative expense

Inspect the source

Entity

DATA STORAGE CORPORATION / CIK 0001419951

Captured

2026-09-20T08:02:59.810Z

SEC response SHA-256

b4ca86e91af39885b856d7d30a3b7cf7dc97e10d579e033c0b729a66116b1ed8

Current SEC company facts · Download the original response snapshot (gzip) · Download the selected JSON

Latest-filed annual-report facts per unit and reporting period at capture time. Duration facts cover 300 to 400 days. This selection can include restatements and is not a point-in-time backtest dataset. Missing concepts are omitted, never zero-filled. Values retain original units and are not currency converted. Extended concepts require compatible unit shapes and at least three reporting ends with changing values within one unit. Constant or incompatible added histories are omitted.

Public company accounting reference, not market prices, returns, an investment recommendation, or ALPHAC performance. Validate a separately constructed return series with the validation API; accounting values are not returns.

Use this in research

A financial period ends before its results become public. Use the filing date as a minimum availability boundary, inspect amendments, and retain the original filing vintage when testing historical signals. This latest-filed selection can contain information unavailable at the time.

These pages do not supply prices, total-return histories, corporate-action adjustments or a tradable universe. Build those inputs separately before evaluating a strategy. A profitable backtest can still reflect selection bias or costs that were left out.

Research methodology · Execution and cost assumptions · Check backtest overfitting

Build with the open-source tools

Use these accounting records as inspectable inputs. When you have constructed a return series, the validation tools can help test its statistical evidence and preserve the result with its limitations.

• Get an API key and run your first validation
• Connect the MCP server to your coding assistant
• Inspect the ALPHAC engine on GitHub
• Read the MCP server source and integration examples

import json
from urllib.request import urlopen

with urlopen("https://canlicapital.com/company-data/0001419951.json") as response:
    record = json.load(response)
print(record["fetched_at"])
print(record["policy"])
for concept in record["concepts"]:
    print(concept["tag"], next(iter(concept["observations"])))