Datasea Intelligent Technology (DTSS) Other Operating Expenses (2016 - 2025)
Datasea Intelligent Technology's Other Operating Expenses was $328,974 in fiscal Q2 2026 (quarter ended Dec 31, 2025), down 19.3% from $407,669 a year earlier and down 16.5% from the prior quarter.
Datasea Intelligent Technology (DTSS) Other Operating Expenses (2016 - 2025) Analysis & Trends
On a trailing twelve-month basis, Datasea Intelligent Technology's Other Operating Expenses was $1.3 million through Dec 31, 2025, down 62.3% year-over-year; for FY2025 (ended Jun 30, 2025), it came in at $1.98 million, down 39.6% from FY2024.
- In earlier fiscal years, Other Operating Expenses was $3.28 million in FY2024 (+780.1%), $372,639 in FY2023 (-72.6%), $1.36 million in FY2022 and -$1,185 in FY2021.
- Quarterly Other Operating Expenses has moved between $45,002 (fiscal Q3 2023) and $1.15 million (fiscal Q2 2024) over five years.
- Compared with a year earlier, Other Operating Expenses has declined for five straight quarters, with growth averaging 35.9% over the last six quarters.
- The best year-over-year quarter for Other Operating Expenses over five years was fiscal Q4 2024 (growth of 504.0%); the worst was fiscal Q3 2025 (a decline of 80.9%).
- Per Business Quant data, DTSS's Other Operating Expenses in the three fiscal quarters before Q2 2026 was $393,817 (Q1 2026), $391,152 (Q4 2025) and $185,354 (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Infosys | 43.52 Bn | 43.57 Bn | 1.60 Bn |
| 2 | Cognizant Technology Solutions | 25.96 Bn | 19.13 Bn | 1.83 Bn |
| 3 | Td Synnex | 20.53 Bn | 14.56 Bn | 1.34 Bn |
| 4 | Cdw | 16.06 Bn | 14.05 Bn | 1.32 Bn |
| 5 | Cgi | 15.14 Bn | 12.92 Bn | - |
| 6 | Arrow Electronics | 11.55 Bn | 10.58 Bn | 1.13 Bn |
| 7 | Avnet | 8.20 Bn | 7.38 Bn | 865.03 Mn |
| 8 | Ingram Micro Holding | 6.32 Bn | 1.92 Bn | 958.68 Mn |
| 9 | EPAM Systems | 5.59 Bn | 1.23 Bn | 429.57 Mn |
| 10 | Datasea Intelligent Technology | 8.22 Mn | 5.30 Mn | 1.19 Mn |
Historic Data
| Date | Value |
|---|---|
| Dec 31, 2025 | 328,974.00 |
| Sep 30, 2025 | 393,817.00 |
| Jun 30, 2025 | 391,152.00 |
| Mar 31, 2025 | 185,354.00 |
| Dec 31, 2024 | 407,669.00 |
| Sep 30, 2024 | 996,049.00 |
| Jun 30, 2024 | 1.07 Mn |
| Mar 31, 2024 | 970,443.00 |
| Dec 31, 2023 | 1.15 Mn |
| Sep 30, 2023 | 84,447.00 |
| Jun 30, 2023 | 177,935.00 |
| Mar 31, 2023 | 45,002.00 |
| Dec 31, 2022 | 45,588.00 |
| Sep 30, 2022 | 104,114.00 |
| Jun 30, 2022 | 745,950.00 |
| Mar 31, 2022 | 225,262.00 |
| Dec 31, 2021 | 225,262.00 |
| Sep 30, 2021 | 230,799.00 |
| Jun 30, 2021 | 272,782.00 |
| Mar 31, 2021 | 121,216.00 |
Datasea Intelligent Technology Other Operating Expenses 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=other-operating-expenses&ticker=DTSS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "other-operating-expenses", "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=other-operating-expenses&ticker=DTSS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();