Datasea Intelligent Technology (DTSS) Current Assets (2015 - 2025)
Datasea Intelligent Technology's Current Assets came in at $3.02 million for fiscal Q2 2026 (quarter ended Dec 31, 2025), up 89.6% from $1.6 million a year earlier and up 11.3% from the prior quarter.
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Analysis
Datasea Intelligent Technology (DTSS) Current Assets (2015 - 2025) Analysis & Trends
At the end of FY2025 (ended Jun 30, 2025), Datasea Intelligent Technology's Current Assets was $2.92 million, up 10.4% from FY2024.
- Current Assets has increased in each of the last four fiscal years, though with a five-year compound annual growth rate of -5.6% (FY2020 to FY2025).
- Going back by fiscal year, Current Assets was $2.65 million in FY2024 (+105.3%), $1.29 million in FY2023 (+2.6%), $1.26 million in FY2022 (+41.9%) and $885,985 in FY2021 (-77.3%).
- The fiscal Q2 2026 figure represents the highest quarterly Current Assets since fiscal Q1 2025.
- Year-over-year, Current Assets increased in four of the last eight quarters, with growth averaging 10.7%.
- The fastest year-over-year change in Current Assets over five years came in fiscal Q1 2024 (growth of 708.1%), and the weakest in fiscal Q1 2023 (a decline of 86.8%).
- Business Quant data shows DTSS's Current Assets at $2.72 million (Q1 2026), $2.92 million (Q4 2025) and $1.99 million (Q3 2025) in the three fiscal quarters before Q2 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Current Assets (Qtr) |
|---|---|---|---|---|---|
| 1 | Infosys | 42.66 Bn | 42.72 Bn | 1.60 Bn | 10.41 Bn |
| 2 | Cognizant Technology Solutions | 25.65 Bn | 18.82 Bn | 1.83 Bn | 7.56 Bn |
| 3 | Td Synnex | 20.51 Bn | 14.54 Bn | 1.34 Bn | 29.59 Bn |
| 4 | Cdw | 16.33 Bn | 14.32 Bn | 1.32 Bn | 9.68 Bn |
| 5 | Cgi | 15.07 Bn | 12.85 Bn | - | 3.62 Bn |
| 6 | Arrow Electronics | 11.72 Bn | 10.75 Bn | 1.13 Bn | 34.99 Bn |
| 7 | Avnet | 8.33 Bn | 7.51 Bn | 865.03 Mn | 13.33 Bn |
| 8 | Ingram Micro Holding | 6.23 Bn | 1.84 Bn | 958.68 Mn | 18.53 Bn |
| 9 | EPAM Systems | 5.55 Bn | 1.19 Bn | 429.57 Mn | 2.22 Bn |
| 10 | Datasea Intelligent Technology | 8.93 Mn | 6.01 Mn | 1.19 Mn | 3.02 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Dec 31, 2025 | 3.02 Mn |
| Sep 30, 2025 | 2.72 Mn |
| Jun 30, 2025 | 2.92 Mn |
| Mar 31, 2025 | 1.99 Mn |
| Dec 31, 2024 | 1.60 Mn |
| Sep 30, 2024 | 7.18 Mn |
| Jun 30, 2024 | 2.65 Mn |
| Mar 31, 2024 | 2.62 Mn |
| Dec 31, 2023 | 4.06 Mn |
| Sep 30, 2023 | 7.91 Mn |
| Jun 30, 2023 | 1.29 Mn |
| Mar 31, 2023 | 1.92 Mn |
| Dec 31, 2022 | 1.33 Mn |
| Sep 30, 2022 | 979,033.00 |
| Jun 30, 2022 | 1.26 Mn |
| Mar 31, 2022 | 7.85 Mn |
| Dec 31, 2021 | 9.13 Mn |
| Sep 30, 2021 | 7.39 Mn |
| Jun 30, 2021 | 885,985.00 |
| Mar 31, 2021 | 1.49 Mn |
API Access
Datasea Intelligent Technology Current 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=current-assets&ticker=DTSS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "current-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=current-assets&ticker=DTSS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();