Datasea Intelligent Technology (DTSS) Capital Expenditures (2015 - 2025)
Datasea Intelligent Technology's Capital Expenditures was $886.00 in fiscal Q4 2025 (quarter ended Jun 30, 2025), down 72.1% from $3,176 a year earlier.
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Analysis
Datasea Intelligent Technology (DTSS) Capital Expenditures (2015 - 2025) Analysis & Trends
For FY2025 (ended Jun 30, 2025), Capital Expenditures at Datasea Intelligent Technology came in at $8,129, up 18.4% from FY2024.
- Capital Expenditures shows a five-year compound annual growth rate of -51.3% (FY2020 to FY2025).
- In earlier fiscal years, Capital Expenditures was $6,868 in FY2024 (+77.0%), $3,881 in FY2023 (-92.4%), $51,340 in FY2022 (-64.0%) and $142,537 in FY2021 (-51.8%).
- Quarterly Capital Expenditures has moved between -$108.00 (fiscal Q3 2023) and $47,376 (fiscal Q2 2021) over five years.
- Compared with a year earlier, Capital Expenditures was higher in four of the last six quarters, with growth averaging 140.4%.
- The best year-over-year quarter for Capital Expenditures over five years was fiscal Q1 2025 (growth of 733.9%); the worst was fiscal Q1 2023 (a decline of 95.6%).
- Per Business Quant data, DTSS's Capital Expenditures in the three fiscal quarters before Q4 2025 was -$12.00 (Q3 2025), $4,503 (Q2 2025) and $2,752 (Q1 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Capex (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 | 99.00 Mn |
| 3 | Td Synnex | 20.53 Bn | 14.56 Bn | 1.34 Bn | 66.82 Mn |
| 4 | Cdw | 16.06 Bn | 14.05 Bn | 1.32 Bn | 27.50 Mn |
| 5 | Cgi | 15.14 Bn | 12.92 Bn | - | -20.01 Mn |
| 6 | Arrow Electronics | 11.55 Bn | 10.58 Bn | 1.13 Bn | 21.14 Mn |
| 7 | Avnet | 8.20 Bn | 7.38 Bn | 865.03 Mn | 16.76 Mn |
| 8 | Ingram Micro Holding | 6.32 Bn | 1.92 Bn | 958.68 Mn | 32.92 Mn |
| 9 | EPAM Systems | 5.59 Bn | 1.23 Bn | 429.57 Mn | 15.21 Mn |
| 10 | Datasea Intelligent Technology | 8.22 Mn | 5.30 Mn | 1.19 Mn | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2025 | 886.00 |
| Mar 31, 2025 | -12.00 |
| Dec 31, 2024 | 4,503.00 |
| Sep 30, 2024 | 2,752.00 |
| Jun 30, 2024 | 3,176.00 |
| Mar 31, 2024 | 9.00 |
| Dec 31, 2023 | 3,353.00 |
| Sep 30, 2023 | 330.00 |
| Jun 30, 2023 | 1,713.00 |
| Mar 31, 2023 | -108.00 |
| Dec 31, 2022 | 1,873.00 |
| Sep 30, 2022 | 403.00 |
| Jun 30, 2022 | 19,152.00 |
| Mar 31, 2022 | 8,401.00 |
| Dec 31, 2021 | 14,631.00 |
| Sep 30, 2021 | 9,156.00 |
| Jun 30, 2021 | 39,483.00 |
| Mar 31, 2021 | 11,840.00 |
| Dec 31, 2020 | 47,376.00 |
| Sep 30, 2020 | 43,838.00 |
API Access
Datasea Intelligent Technology Capital Expenditures 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=capital-expenditures&ticker=DTSS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "capital-expenditures", "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=capital-expenditures&ticker=DTSS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();