Dynatrace (DT) Change in Accured Expenses (2018 - 2026)
Dynatrace's Change in Accured Expenses was -$9.02 million in fiscal Q1 2027 (quarter ended Jun 30, 2026), compared with -$73.11 million a year earlier.
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Analysis
Dynatrace (DT) Change in Accured Expenses (2018 - 2026) Analysis & Trends
On a trailing twelve-month basis, Dynatrace's Change in Accured Expenses was $89.98 million through Jun 30, 2026, up 145.3% year-over-year; for FY2026 (ended Mar 31, 2026), it was $25.9 million, down 17.9% from FY2025.
- Change in Accured Expenses has now declined for three consecutive fiscal years, with a five-year compound annual growth rate of -0.5% (FY2021 to FY2026).
- In earlier fiscal years, Change in Accured Expenses was $31.53 million in FY2025 (-16.8%), $37.9 million in FY2024 (-35.4%), $58.68 million in FY2023 (+63.2%) and $35.95 million in FY2022 (+35.2%).
- Quarterly Change in Accured Expenses has moved between -$78.27 million (fiscal Q1 2025) and $61.92 million (fiscal Q4 2024) over five years.
- Compared with a year earlier, Change in Accured Expenses was higher in two of the last six quarters, with growth averaging 94.4%.
- The best year-over-year quarter for Change in Accured Expenses over five years was fiscal Q2 2025 (growth of 647.2%); the worst was fiscal Q3 2024 (a decline of 72.7%).
- Per Business Quant data, DT's Change in Accured Expenses in the three fiscal quarters before Q1 2027 was $56.34 million (Q4 2026), $3.31 million (Q3 2026) and $39.36 million (Q2 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accured Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 328.64 Bn | 313.71 Bn | 2.30 Bn | 369.00 Mn |
| 2 | CrowdStrike Holdings | 276.50 Bn | 256.94 Bn | 1.10 Bn | 72.38 Mn |
| 3 | Fortinet | 132.74 Bn | 118.67 Bn | 1.64 Bn | 75.10 Mn |
| 4 | Snowflake | 120.19 Bn | 107.50 Bn | 1.04 Bn | 108.85 Mn |
| 5 | Datadog | 99.51 Bn | 81.15 Bn | 881.34 Mn | 6.98 Mn |
| 6 | Okta | 35.35 Bn | 25.44 Bn | 641.00 Mn | -2.00 Mn |
| 7 | Axon Enterprise | 33.58 Bn | 28.10 Bn | 546.45 Mn | 256.58 Mn |
| 8 | Zscaler | 32.06 Bn | 18.18 Bn | - | - |
| 9 | MongoDB | 28.84 Bn | 19.30 Bn | 569.77 Mn | 43.09 Mn |
| 10 | Dynatrace | 17.22 Bn | 12.43 Bn | 451.10 Mn | -9.02 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | -9.02 Mn |
| Mar 31, 2026 | 56.34 Mn |
| Dec 31, 2025 | 3.31 Mn |
| Sep 30, 2025 | 39.36 Mn |
| Jun 30, 2025 | -73.11 Mn |
| Mar 31, 2025 | 59.14 Mn |
| Dec 31, 2024 | 2.87 Mn |
| Sep 30, 2024 | 47.79 Mn |
| Jun 30, 2024 | -78.27 Mn |
| Mar 31, 2024 | 61.92 Mn |
| Dec 31, 2023 | 9.22 Mn |
| Sep 30, 2023 | 6.40 Mn |
| Jun 30, 2023 | -39.64 Mn |
| Mar 31, 2023 | 39.32 Mn |
| Dec 31, 2022 | 33.79 Mn |
| Sep 30, 2022 | 15.39 Mn |
| Jun 30, 2022 | -29.82 Mn |
| Mar 31, 2022 | 24.96 Mn |
| Dec 31, 2021 | 20.11 Mn |
| Sep 30, 2021 | 18.26 Mn |
API Access
Dynatrace Change in Accured 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=change-in-accured-expenses&ticker=DT&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "ticker": "DT", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=change-in-accured-expenses&ticker=DT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();