Datasea Intelligent Technology (DTSS) Net Margin (2016 - 2025)
Datasea Intelligent Technology's Net Margin came in at -4.16% for fiscal Q2 2026 (quarter ended Dec 31, 2025), up 1.42 percentage points from -5.57% a year earlier but down 2.70 percentage points from the prior quarter.
Datasea Intelligent Technology (DTSS) Net Margin (2016 - 2025) Analysis & Trends
Over the trailing twelve months to Dec 31, 2025, Datasea Intelligent Technology reported Net Margin of -4.80%, up 21.89 percentage points year-over-year; for FY2025 (ended Jun 30, 2025), it was -7.11%, up 40.36 percentage points from FY2024.
- Net Margin carries a five-year change of +124.36 percentage points (FY2020 to FY2025).
- Going back by fiscal year, Net Margin was -47.46% in FY2024 (-307.85 pp), 260.39% in FY2023 (+222.22 pp), 38.17% in FY2022 (+38.17 pp) and 0.00% in FY2021 (+131.47 pp).
- The five-year range for quarterly Net Margin is -13730.68% (fiscal Q4 2021) to 6898.11% (fiscal Q3 2021).
- Year-over-year, Net Margin has increased for five consecutive quarters, with an average year-over-year change of +918.97 percentage points over the last eight quarters.
- The fastest year-over-year change in Net Margin over five years came in fiscal Q4 2022 (a gain of 15118.13 percentage points), and the weakest in fiscal Q1 2022 (a drop of 9393.39 percentage points).
- Business Quant data shows DTSS's Net Margin at -1.46% (Q1 2026), -1.06% (Q4 2025) and -17.22% (Q3 2025) in the three fiscal quarters before Q2 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Net Margin (Qtr) |
|---|---|---|---|---|---|
| 1 | Infosys | 42.66 Bn | 42.72 Bn | 1.60 Bn | 16.16% |
| 2 | Cognizant Technology Solutions | 25.65 Bn | 18.82 Bn | 1.83 Bn | 11.60% |
| 3 | Td Synnex | 20.51 Bn | 14.54 Bn | 1.34 Bn | 1.71% |
| 4 | Cdw | 16.33 Bn | 14.32 Bn | 1.32 Bn | 4.18% |
| 5 | Cgi | 15.07 Bn | 12.85 Bn | - | 11.09% |
| 6 | Arrow Electronics | 11.72 Bn | 10.75 Bn | 1.13 Bn | 2.73% |
| 7 | Avnet | 8.33 Bn | 7.51 Bn | 865.03 Mn | 1.53% |
| 8 | Ingram Micro Holding | 6.23 Bn | 1.84 Bn | 958.68 Mn | 0.76% |
| 9 | EPAM Systems | 5.55 Bn | 1.19 Bn | 429.57 Mn | 7.28% |
| 10 | Datasea Intelligent Technology | 8.93 Mn | 6.01 Mn | 1.19 Mn | -4.16% |
Historic Data
| Date | Value |
|---|---|
| Dec 31, 2025 | -4.16% |
| Sep 30, 2025 | -1.46% |
| Jun 30, 2025 | -1.06% |
| Mar 31, 2025 | -17.22% |
| Dec 31, 2024 | -5.57% |
| Sep 30, 2024 | -9.31% |
| Jun 30, 2024 | -123.29% |
| Mar 31, 2024 | -299.47% |
| Dec 31, 2023 | -16.15% |
| Sep 30, 2023 | -0.32% |
| Jun 30, 2023 | 391.38% |
| Mar 31, 2023 | -7,750.54% |
| Dec 31, 2022 | -985.22% |
| Sep 30, 2022 | 115.09% |
| Jun 30, 2022 | 1,387.45% |
| Mar 31, 2022 | -19.27% |
| Dec 31, 2021 | -19.23% |
| Sep 30, 2021 | 214.56% |
| Jun 30, 2021 | -13,730.68% |
| Mar 31, 2021 | 6,898.11% |
Datasea Intelligent Technology Net Margin API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=net-margin&ticker=DTSS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "net-margin", "ticker": "DTSS", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=net-margin&ticker=DTSS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();