Datasea Intelligent Technology (DTSS) Receivables (2017 - 2025)
Datasea Intelligent Technology's Receivables was $1.75 million in fiscal Q2 2026 (quarter ended Dec 31, 2025), up 163.0% from $667,271 a year earlier and up 7.4% from the prior quarter.
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Analysis
Datasea Intelligent Technology (DTSS) Receivables (2017 - 2025) Analysis & Trends
At the end of FY2025 (ended Jun 30, 2025), Receivables at Datasea Intelligent Technology came in at $1.83 million, up 54.5% from FY2024.
- Receivables shows a five-year compound annual growth rate of 16.5% (FY2020 to FY2025).
- In earlier fiscal years, Receivables was $1.19 million in FY2024 (-24.3%), $1.57 million in FY2023 (+117.4%), $720,260 in FY2022 (-15.7%) and $854,476 in FY2021 (unchanged).
- Quarterly Receivables has moved between $506,005 (fiscal Q3 2025) and $6.1 million (fiscal Q3 2022) over five years.
- Compared with a year earlier, Receivables was higher in five of the last eight quarters, with growth averaging 26.5%.
- The best year-over-year quarter for Receivables over five years was fiscal Q2 2022 (growth of 926.2%); the worst was fiscal Q2 2023 (a decline of 81.8%).
- Per Business Quant data, DTSS's Receivables in the three fiscal quarters before Q2 2026 was $1.63 million (Q1 2026), $1.83 million (Q4 2025) and $506,005 (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Receivables (Qtr) |
|---|---|---|---|---|---|
| 1 | Infosys | 42.66 Bn | 42.72 Bn | 1.60 Bn | 5.33 Bn |
| 2 | Cognizant Technology Solutions | 25.65 Bn | 18.82 Bn | 1.83 Bn | 4.78 Bn |
| 3 | Td Synnex | 20.51 Bn | 14.54 Bn | 1.34 Bn | 13.00 Bn |
| 4 | Cdw | 16.33 Bn | 14.32 Bn | 1.32 Bn | 10.28 Bn |
| 5 | Cgi | 15.07 Bn | 12.85 Bn | - | 1.14 Bn |
| 6 | Arrow Electronics | 11.72 Bn | 10.75 Bn | 1.13 Bn | 28.01 Bn |
| 7 | Avnet | 8.33 Bn | 7.51 Bn | 865.03 Mn | 6.88 Bn |
| 8 | Ingram Micro Holding | 6.23 Bn | 1.84 Bn | 958.68 Mn | 10.68 Bn |
| 9 | EPAM Systems | 5.55 Bn | 1.19 Bn | 429.57 Mn | 1.27 Bn |
| 10 | Datasea Intelligent Technology | 8.93 Mn | 6.01 Mn | 1.19 Mn | 1.75 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Dec 31, 2025 | 1.75 Mn |
| Sep 30, 2025 | 1.63 Mn |
| Jun 30, 2025 | 1.83 Mn |
| Mar 31, 2025 | 506,005.00 |
| Dec 31, 2024 | 667,271.00 |
| Sep 30, 2024 | 4.00 Mn |
| Jun 30, 2024 | 1.19 Mn |
| Mar 31, 2024 | 1.50 Mn |
| Dec 31, 2023 | 1.53 Mn |
| Sep 30, 2023 | 1.90 Mn |
| Jun 30, 2023 | 716,575.00 |
| Mar 31, 2023 | 1.49 Mn |
| Dec 31, 2022 | 1.06 Mn |
| Sep 30, 2022 | 1.04 Mn |
| Jun 30, 2022 | 720,260.00 |
| Mar 31, 2022 | 6.10 Mn |
| Dec 31, 2021 | 5.80 Mn |
| Sep 30, 2021 | 1.28 Mn |
| Jun 30, 2021 | 854,476.00 |
| Mar 31, 2021 | 854,476.00 |
API Access
Datasea Intelligent Technology Receivables 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=receivables&ticker=DTSS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "receivables", "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=receivables&ticker=DTSS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();