Datasea Intelligent Technology (DTSS) Assets (2015 - 2025)
Datasea Intelligent Technology's Assets was $8.64 million in fiscal Q2 2026 (quarter ended Dec 31, 2025), up 46.4% from $5.9 million a year earlier and up 12.4% from the prior quarter.
Datasea Intelligent Technology (DTSS) Assets (2015 - 2025) Analysis & Trends
At the end of FY2025 (ended Jun 30, 2025), Assets at Datasea Intelligent Technology came in at $6.74 million, up 104.6% from FY2024.
- Assets shows a five-year compound annual growth rate of 6.5% (FY2020 to FY2025).
- In earlier fiscal years, Assets was $3.29 million in FY2024 (+19.5%), $2.75 million in FY2023 (-26.7%), $3.76 million in FY2022 (-3.6%) and $3.9 million in FY2021 (-20.7%).
- The fiscal Q2 2026 figure marks the highest quarterly Assets since fiscal Q1 2024.
- Compared with a year earlier, Assets was higher in five of the last eight quarters, with growth averaging 32.4%.
- The best year-over-year quarter for Assets over five years was fiscal Q1 2024 (growth of 185.1%); the worst was fiscal Q2 2023 (a decline of 72.6%).
- Per Business Quant data, DTSS's Assets in the three fiscal quarters before Q2 2026 was $7.69 million (Q1 2026), $6.74 million (Q4 2025) and $6.15 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Assets (Qtr) |
|---|---|---|---|---|---|
| 1 | Infosys | 42.66 Bn | 42.72 Bn | 1.60 Bn | 16.36 Bn |
| 2 | Cognizant Technology Solutions | 25.65 Bn | 18.82 Bn | 1.83 Bn | 20.83 Bn |
| 3 | Td Synnex | 20.51 Bn | 14.54 Bn | 1.34 Bn | 38.51 Bn |
| 4 | Cdw | 16.33 Bn | 14.32 Bn | 1.32 Bn | 17.25 Bn |
| 5 | Cgi | 15.07 Bn | 12.85 Bn | - | - |
| 6 | Arrow Electronics | 11.72 Bn | 10.75 Bn | 1.13 Bn | 38.38 Bn |
| 7 | Avnet | 8.33 Bn | 7.51 Bn | 865.03 Mn | 15.43 Bn |
| 8 | Ingram Micro Holding | 6.23 Bn | 1.84 Bn | 958.68 Mn | 21.53 Bn |
| 9 | EPAM Systems | 5.55 Bn | 1.19 Bn | 429.57 Mn | 4.57 Bn |
| 10 | Datasea Intelligent Technology | 8.93 Mn | 6.01 Mn | 1.19 Mn | 8.64 Mn |
Historic Data
| Date | Value |
|---|---|
| Dec 31, 2025 | 8.64 Mn |
| Sep 30, 2025 | 7.69 Mn |
| Jun 30, 2025 | 6.74 Mn |
| Mar 31, 2025 | 6.15 Mn |
| Dec 31, 2024 | 5.90 Mn |
| Sep 30, 2024 | 7.96 Mn |
| Jun 30, 2024 | 3.29 Mn |
| Mar 31, 2024 | 3.37 Mn |
| Dec 31, 2023 | 4.94 Mn |
| Sep 30, 2023 | 8.82 Mn |
| Jun 30, 2023 | 2.75 Mn |
| Mar 31, 2023 | 3.38 Mn |
| Dec 31, 2022 | 3.26 Mn |
| Sep 30, 2022 | 3.09 Mn |
| Jun 30, 2022 | 3.76 Mn |
| Mar 31, 2022 | 10.43 Mn |
| Dec 31, 2021 | 11.87 Mn |
| Sep 30, 2021 | 10.17 Mn |
| Jun 30, 2021 | 3.90 Mn |
| Mar 31, 2021 | 4.58 Mn |
Datasea Intelligent Technology Assets 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=assets&ticker=DTSS&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "assets", "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=assets&ticker=DTSS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();