Datasea Intelligent Technology (DTSS) Revenue (2016 - 2025)
Datasea Intelligent Technology's Revenue came in at $13 million for fiscal Q2 2026 (quarter ended Dec 31, 2025), down 36.5% from $20.46 million a year earlier and down 5.9% from the prior quarter.
Datasea Intelligent Technology (DTSS) Revenue (2016 - 2025) Analysis & Trends
Over the trailing twelve months to Dec 31, 2025, Datasea Intelligent Technology reported Revenue of $56.89 million, up 20.3% year-over-year; for FY2025 (ended Jun 30, 2025), it was $71.62 million, up 198.7% from FY2024.
- Revenue carries a five-year compound annual growth rate of 119.2% (FY2020 to FY2025).
- Going back by fiscal year, Revenue was $23.98 million in FY2024 (+558.6%), $3.64 million in FY2023 (-78.7%), $17.08 million in FY2022 and $175,138 in FY2021 (-87.6%).
- The five-year range for quarterly Revenue is $17,686 (fiscal Q3 2021) to $21.08 million (fiscal Q1 2025).
- Year-over-year, Revenue increased in five of the last seven quarters, with growth averaging 177.7%.
- The fastest year-over-year change in Revenue over five years came in fiscal Q3 2025 (growth of 648.7%), and the weakest in fiscal Q3 2023 (a decline of 98.7%).
- Business Quant data shows DTSS's Revenue at $13.81 million (Q1 2026), $19.73 million (Q4 2025) and $10.35 million (Q3 2025) in the three fiscal quarters before Q2 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Revenue (Qtr) |
|---|---|---|---|---|---|
| 1 | Infosys | 43.52 Bn | 43.57 Bn | 1.60 Bn | 5.08 Bn |
| 2 | Cognizant Technology Solutions | 25.96 Bn | 19.13 Bn | 1.83 Bn | 5.48 Bn |
| 3 | Td Synnex | 20.53 Bn | 14.56 Bn | 1.34 Bn | 19.57 Bn |
| 4 | Cdw | 16.06 Bn | 14.05 Bn | 1.32 Bn | 6.57 Bn |
| 5 | Cgi | 15.14 Bn | 12.92 Bn | - | 3.03 Bn |
| 6 | Arrow Electronics | 11.55 Bn | 10.58 Bn | 1.13 Bn | 9.99 Bn |
| 7 | Avnet | 8.20 Bn | 7.38 Bn | 865.03 Mn | 8.30 Bn |
| 8 | Ingram Micro Holding | 6.32 Bn | 1.92 Bn | 958.68 Mn | 14.53 Bn |
| 9 | EPAM Systems | 5.59 Bn | 1.23 Bn | 429.57 Mn | 1.41 Bn |
| 10 | Datasea Intelligent Technology | 8.22 Mn | 5.30 Mn | 1.19 Mn | 13.00 Mn |
Historic Data
| Date | Value |
|---|---|
| Dec 31, 2025 | 13.00 Mn |
| Sep 30, 2025 | 13.81 Mn |
| Jun 30, 2025 | 19.73 Mn |
| Mar 31, 2025 | 10.35 Mn |
| Dec 31, 2024 | 20.46 Mn |
| Sep 30, 2024 | 21.08 Mn |
| Jun 30, 2024 | 4.36 Mn |
| Mar 31, 2024 | 1.38 Mn |
| Dec 31, 2023 | 11.35 Mn |
| Sep 30, 2023 | 6.88 Mn |
| Jun 30, 2023 | 3.42 Mn |
| Mar 31, 2023 | 84,555.00 |
| Dec 31, 2022 | 131,459.00 |
| Sep 30, 2022 | 1.16 Mn |
| Jun 30, 2022 | 786,764.00 |
| Mar 31, 2022 | 6.64 Mn |
| Dec 31, 2021 | 6.64 Mn |
| Sep 30, 2021 | 671,130.00 |
| Jun 30, 2021 | 22,213.00 |
| Mar 31, 2021 | 17,686.00 |
Datasea Intelligent Technology Revenue 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=revenue&ticker=DTSS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "revenue", "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=revenue&ticker=DTSS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();