Dynatrace (DT) Accumulated Expenses (2019 - 2026)
Dynatrace's Accumulated Expenses came in at $287.49 million for fiscal Q1 2027 (quarter ended Jun 30, 2026), up 38.9% from $207.02 million a year earlier but down 4.9% from the prior quarter.
Powered by 
Analysis
Dynatrace (DT) Accumulated Expenses (2019 - 2026) Analysis & Trends
At the end of FY2026 (ended Mar 31, 2026), Dynatrace's Accumulated Expenses was $302.26 million, up 19.7% from FY2025.
- Accumulated Expenses has increased in each of the last seven fiscal years, with a five-year compound annual growth rate of 20.4% (FY2021 to FY2026).
- Going back by fiscal year, Accumulated Expenses was $252.5 million in FY2025 (+8.1%), $233.68 million in FY2024 (+24.0%), $188.38 million in FY2023 (+33.1%) and $141.56 million in FY2022 (+18.4%).
- The five-year range for quarterly Accumulated Expenses is $105.42 million (fiscal Q2 2022) to $302.26 million (fiscal Q4 2026).
- Year-over-year, Accumulated Expenses has increased for 26 consecutive quarters, with growth averaging 22.2% over the last eight quarters.
- The year-over-year growth in Accumulated Expenses has ranged between 8.1% (fiscal Q4 2025) and 42.3% (fiscal Q2 2025) over the last five years.
- Business Quant data shows DT's Accumulated Expenses at $302.26 million (Q4 2026), $240.02 million (Q3 2026) and $230.03 million (Q2 2026) in the three fiscal quarters before Q1 2027.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Palo Alto Networks | 323.81 Bn | 308.88 Bn | 2.30 Bn |
| 2 | CrowdStrike Holdings | 271.09 Bn | 251.53 Bn | 1.10 Bn |
| 3 | Fortinet | 131.14 Bn | 117.07 Bn | 1.64 Bn |
| 4 | Snowflake | 119.71 Bn | 107.03 Bn | 1.04 Bn |
| 5 | Datadog | 98.30 Bn | 79.94 Bn | 881.34 Mn |
| 6 | Okta | 34.95 Bn | 25.05 Bn | 641.00 Mn |
| 7 | Axon Enterprise | 34.32 Bn | 28.85 Bn | 546.45 Mn |
| 8 | Zscaler | 32.52 Bn | 18.64 Bn | - |
| 9 | Baidu | 29.56 Bn | -44.07 Bn | 1.47 Mn |
| 10 | Dynatrace | 16.77 Bn | 11.99 Bn | 451.10 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 287.49 Mn |
| Mar 31, 2026 | 302.26 Mn |
| Dec 31, 2025 | 240.02 Mn |
| Sep 30, 2025 | 230.03 Mn |
| Jun 30, 2025 | 207.02 Mn |
| Mar 31, 2025 | 252.50 Mn |
| Dec 31, 2024 | 213.13 Mn |
| Sep 30, 2024 | 208.83 Mn |
| Jun 30, 2024 | 169.90 Mn |
| Mar 31, 2024 | 233.68 Mn |
| Dec 31, 2023 | 171.93 Mn |
| Sep 30, 2023 | 146.78 Mn |
| Jun 30, 2023 | 156.15 Mn |
| Mar 31, 2023 | 188.38 Mn |
| Dec 31, 2022 | 154.08 Mn |
| Sep 30, 2022 | 129.98 Mn |
| Jun 30, 2022 | 114.21 Mn |
| Mar 31, 2022 | 141.56 Mn |
| Dec 31, 2021 | 116.15 Mn |
| Sep 30, 2021 | 105.42 Mn |
API Access
Dynatrace 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=accumulated-expenses&ticker=DT&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-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=accumulated-expenses&ticker=DT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();