Datasea Intelligent Technology (DTSS) Other Accumulated Expenses (2019 - 2026)
Datasea Intelligent Technology's Other Accumulated Expenses was $675,930 in fiscal Q2 2026 (quarter ended Dec 31, 2025), up 35.3% from $499,637 a year earlier and up 7.5% from the prior quarter.
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Analysis
Datasea Intelligent Technology (DTSS) Other Accumulated Expenses (2019 - 2026) Analysis & Trends
At the end of FY2025 (ended Jun 30, 2025), Other Accumulated Expenses at Datasea Intelligent Technology came in at $547,706, up 213.6% from FY2024.
- Other Accumulated Expenses shows a five-year compound annual growth rate of 88.2% (FY2020 to FY2025).
- In earlier fiscal years, Other Accumulated Expenses was $174,668 in FY2024 (-57.8%), $413,795 in FY2023 (+102.2%), $204,662 in FY2022 (-23.8%) and $268,527 in FY2021.
- The fiscal Q2 2026 figure marks the highest quarterly Other Accumulated Expenses since fiscal Q1 2025.
- Compared with a year earlier, Other Accumulated Expenses was higher in five of the last eight quarters, with growth averaging 209.9%.
- The best year-over-year quarter for Other Accumulated Expenses over five years was fiscal Q3 2025 (growth of 776.8%); the worst was fiscal Q3 2023 (a decline of 71.9%).
- Per Business Quant data, DTSS's Other Accumulated Expenses in the three fiscal quarters before Q2 2026 was $628,729 (Q1 2026), $547,706 (Q4 2025) and $476,644 (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Infosys | 44.69 Bn | 44.75 Bn | 1.60 Bn |
| 2 | Cognizant Technology Solutions | 26.45 Bn | 19.61 Bn | 1.83 Bn |
| 3 | Td Synnex | 22.21 Bn | 16.36 Bn | 1.43 Bn |
| 4 | Cdw | 16.70 Bn | 14.69 Bn | 1.32 Bn |
| 5 | Cgi | 15.63 Bn | 13.41 Bn | - |
| 6 | Arrow Electronics | 12.33 Bn | 11.35 Bn | 1.13 Bn |
| 7 | Avnet | 8.78 Bn | 7.96 Bn | 865.03 Mn |
| 8 | Ingram Micro Holding | 6.70 Bn | 2.31 Bn | 958.68 Mn |
| 9 | EPAM Systems | 5.58 Bn | 1.22 Bn | 429.57 Mn |
| 10 | Datasea Intelligent Technology | 13.66 Mn | -441.93 Bn | 1.19 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | -16,084.31 Bn |
| Dec 31, 2025 | 675,930.00 |
| Sep 30, 2025 | 628,729.00 |
| Jun 30, 2025 | 547,706.00 |
| Mar 31, 2025 | 476,644.00 |
| Dec 31, 2024 | 499,637.00 |
| Sep 30, 2024 | 1.33 Mn |
| Jun 30, 2024 | 174,668.00 |
| Mar 31, 2024 | 54,364.00 |
| Dec 31, 2023 | 72,612.00 |
| Sep 30, 2023 | 416,446.00 |
| Jun 30, 2023 | 413,795.00 |
| Mar 31, 2023 | 95,884.00 |
| Dec 31, 2022 | 132,463.00 |
| Sep 30, 2022 | 126,810.00 |
| Jun 30, 2022 | 204,662.00 |
| Mar 31, 2022 | 341,700.00 |
| Dec 31, 2021 | 352,913.00 |
| Sep 30, 2021 | 366,147.00 |
| Jun 30, 2021 | 268,527.00 |
API Access
Datasea Intelligent Technology Other Accumulated Expenses 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=other-accumulated-expenses&ticker=DTSS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "other-accumulated-expenses", "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=other-accumulated-expenses&ticker=DTSS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();