Datasea Intelligent Technology (DTSS) Total Liabilities (2015 - 2025)
Datasea Intelligent Technology (DTSS) posted Total Liabilities of $5.16 million for fiscal Q2 2026 (quarter ended Dec 31, 2025), up 93.5% from $2.67 million a year earlier and up 10.6% from the prior quarter.
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Analysis
Datasea Intelligent Technology (DTSS) Total Liabilities (2015 - 2025) Analysis & Trends
At the end of FY2025 (ended Jun 30, 2025), Datasea Intelligent Technology's Total Liabilities came in at $3.78 million, up 7.2% from FY2024.
- Annual Total Liabilities shows a five-year compound annual growth rate of 29.7% (FY2020 to FY2025).
- In prior fiscal years, Datasea Intelligent Technology's Total Liabilities was $3.53 million in FY2024 (-43.8%), $6.27 million in FY2023 (+381.9%), $1.3 million in FY2022 (-63.6%) and $3.58 million in FY2021 (+246.9%).
- The fiscal Q2 2026 figure stands as the highest quarterly Total Liabilities since fiscal Q4 2023.
- On a year-over-year basis, Total Liabilities has increased in each of the last five quarters, with growth averaging 9.1% over the last eight quarters.
- The strongest year-over-year quarter for Total Liabilities in the past five years was fiscal Q4 2023, with growth of 381.9%; the weakest was fiscal Q4 2022, with a decline of 63.6%.
- According to Business Quant data, Total Liabilities for the three prior fiscal quarters was $4.67 million (Q1 2026), $3.78 million (Q4 2025) and $3.31 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Infosys | 42.66 Bn | 42.72 Bn | 1.60 Bn | 6.69 Bn |
| 2 | Cognizant Technology Solutions | 25.65 Bn | 18.82 Bn | 1.83 Bn | 6.36 Bn |
| 3 | Td Synnex | 20.51 Bn | 14.54 Bn | 1.34 Bn | 29.56 Bn |
| 4 | Cdw | 16.33 Bn | 14.32 Bn | 1.32 Bn | 14.81 Bn |
| 5 | Cgi | 15.07 Bn | 12.85 Bn | - | - |
| 6 | Arrow Electronics | 11.72 Bn | 10.75 Bn | 1.13 Bn | 31.30 Bn |
| 7 | Avnet | 8.33 Bn | 7.51 Bn | 865.03 Mn | 10.40 Bn |
| 8 | Ingram Micro Holding | 6.23 Bn | 1.84 Bn | 958.68 Mn | 17.25 Bn |
| 9 | EPAM Systems | 5.55 Bn | 1.19 Bn | 429.57 Mn | 1.05 Bn |
| 10 | Datasea Intelligent Technology | 8.93 Mn | 6.01 Mn | 1.19 Mn | 5.16 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Dec 31, 2025 | 5.16 Mn |
| Sep 30, 2025 | 4.67 Mn |
| Jun 30, 2025 | 3.78 Mn |
| Mar 31, 2025 | 3.31 Mn |
| Dec 31, 2024 | 2.67 Mn |
| Sep 30, 2024 | 3.85 Mn |
| Jun 30, 2024 | 3.53 Mn |
| Mar 31, 2024 | 2.12 Mn |
| Dec 31, 2023 | 2.34 Mn |
| Sep 30, 2023 | 4.44 Mn |
| Jun 30, 2023 | 6.27 Mn |
| Mar 31, 2023 | 5.58 Mn |
| Dec 31, 2022 | 4.23 Mn |
| Sep 30, 2022 | 1.85 Mn |
| Jun 30, 2022 | 1.30 Mn |
| Mar 31, 2022 | 5.90 Mn |
| Dec 31, 2021 | 6.30 Mn |
| Sep 30, 2021 | 3.45 Mn |
| Jun 30, 2021 | 3.58 Mn |
| Mar 31, 2021 | 2.67 Mn |
API Access
Datasea Intelligent Technology Total Liabilities 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=total-liabilities&ticker=DTSS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "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=total-liabilities&ticker=DTSS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();