Datasea Intelligent Technology (DTSS) Total Debt (2018 - 2025)
Datasea Intelligent Technology's Total Debt was $7.4 million in fiscal Q2 2026 (quarter ended Dec 31, 2025), up 560.6% from $1.12 million a year earlier and up 28.2% from the prior quarter.
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Analysis
Datasea Intelligent Technology (DTSS) Total Debt (2018 - 2025) Analysis & Trends
At the end of FY2025 (ended Jun 30, 2025), Total Debt at Datasea Intelligent Technology came in at $2.37 million, up 79.3% from FY2024.
- Total Debt shows a four-year compound annual growth rate of -5.5% (FY2021 to FY2025).
- In earlier fiscal years, Total Debt was $1.32 million in FY2024 (-47.0%), $2.5 million in FY2023, $184,281 in FY2022 (-93.8%) and $2.97 million in FY2021.
- The fiscal Q2 2026 figure marks the highest quarterly Total Debt in data going back to fiscal Q4 2018.
- Compared with a year earlier, Total Debt has increased for four straight quarters, with growth averaging 161.0% over the last eight quarters.
- The best year-over-year quarter for Total Debt over five years was fiscal Q2 2026 (growth of 560.6%); the worst was fiscal Q4 2022 (a decline of 93.8%).
- Per Business Quant data, DTSS's Total Debt in the three fiscal quarters before Q2 2026 was $5.77 million (Q1 2026), $2.37 million (Q4 2025) and $2.79 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Debt (Qtr) |
|---|---|---|---|---|---|
| 1 | Infosys | 42.66 Bn | 42.72 Bn | 1.60 Bn | 2.24 Bn |
| 2 | Cognizant Technology Solutions | 25.65 Bn | 18.82 Bn | 1.83 Bn | 1.56 Bn |
| 3 | Td Synnex | 20.51 Bn | 14.54 Bn | 1.34 Bn | 4.72 Bn |
| 4 | Cdw | 16.33 Bn | 14.32 Bn | 1.32 Bn | 5.82 Bn |
| 5 | Cgi | 15.07 Bn | 12.85 Bn | - | 2.66 Bn |
| 6 | Arrow Electronics | 11.72 Bn | 10.75 Bn | 1.13 Bn | 2.17 Bn |
| 7 | Avnet | 8.33 Bn | 7.51 Bn | 865.03 Mn | 3.23 Bn |
| 8 | Ingram Micro Holding | 6.23 Bn | 1.84 Bn | 958.68 Mn | 3.80 Bn |
| 9 | EPAM Systems | 5.55 Bn | 1.19 Bn | 429.57 Mn | 25.00 Mn |
| 10 | Datasea Intelligent Technology | 8.93 Mn | 6.01 Mn | 1.19 Mn | 7.40 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Dec 31, 2025 | 7.40 Mn |
| Sep 30, 2025 | 5.77 Mn |
| Jun 30, 2025 | 2.37 Mn |
| Mar 31, 2025 | 2.79 Mn |
| Dec 31, 2024 | 1.12 Mn |
| Sep 30, 2024 | 1.15 Mn |
| Jun 30, 2024 | 1.32 Mn |
| Mar 31, 2024 | 482,499.00 |
| Dec 31, 2023 | 2.66 Mn |
| Sep 30, 2023 | 2.55 Mn |
| Jun 30, 2023 | 2.50 Mn |
| Mar 31, 2023 | 1.78 Mn |
| Dec 31, 2022 | 1.76 Mn |
| Sep 30, 2022 | 866,644.00 |
| Jun 30, 2022 | 184,281.00 |
| Dec 31, 2021 | 1.49 Mn |
| Sep 30, 2021 | 2.47 Mn |
| Jun 30, 2021 | 2.97 Mn |
| Mar 31, 2021 | 1.48 Mn |
| Jun 30, 2019 | 86,733.00 |
API Access
Datasea Intelligent Technology Total Debt 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-debt&ticker=DTSS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-debt", "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-debt&ticker=DTSS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();