Data I (DAIO) Shares Outstanding (Entity) (2010 - 2026)
Data I (DAIO) posted Shares Outstanding (Entity) of 10.4 million for Q2 2026, up 10.9% from 9.37 million a year earlier and up 10.7% from the prior quarter.
Data I (DAIO) Shares Outstanding (Entity) (2010 - 2026) Analysis & Trends
For FY2025, Data I's Shares Outstanding (Entity) came in at 9.39 million, up 1.7% from FY2024.
- Annual Shares Outstanding (Entity) has increased for six consecutive years, with a five-year compound annual growth rate of 2.2% (FY2020 to FY2025).
- In prior years, Data I's Shares Outstanding (Entity) was 9.24 million in FY2024 (+2.4%), 9.02 million in FY2023 (+2.3%), 8.82 million in FY2022 (+2.3%) and 8.62 million in FY2021 (+2.4%).
- The Q2 2026 figure stands as the highest quarterly Shares Outstanding (Entity) in data going back to Q2 2010.
- On a year-over-year basis, Shares Outstanding (Entity) has increased in each of the last 24 quarters, with growth averaging 3.1% over the last eight quarters.
- The year-over-year growth in Shares Outstanding (Entity) has ranged between 1.7% (Q1 2026) and 10.9% (Q2 2026) over the last five years.
- According to Business Quant data, Shares Outstanding (Entity) for the three prior quarters was 9.39 million (Q1 2026), 9.39 million (Q4 2025) and 9.39 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Shares Outstanding (Entity.) (Qtr) |
|---|---|---|---|---|---|
| 1 | Apple | 4,865.08 Bn | 4,612.57 Bn | 54.77 Bn | 14.61 Bn |
| 2 | Cisco Systems | 424.71 Bn | 360.64 Bn | 11.06 Bn | 3.95 Bn |
| 3 | Dell Technologies | 344.52 Bn | 300.28 Bn | 9.83 Bn | 640.00 Mn |
| 4 | Arista Networks | 256.79 Bn | 210.25 Bn | 1.91 Bn | 1.26 Bn |
| 5 | Sandisk | 254.02 Bn | 242.55 Bn | 7.58 Bn | 146.00 Mn |
| 6 | Seagate Technology Holdings | 209.18 Bn | 204.17 Bn | 1.90 Bn | 226.79 Mn |
| 7 | Western Digital | 164.06 Bn | 152.19 Bn | 2.03 Bn | 361.00 Mn |
| 8 | Sony | 144.83 Bn | 95.22 Bn | 6.53 Bn | - |
| 9 | Lumentum Holdings | 86.05 Bn | 77.87 Bn | 477.30 Mn | 88.60 Mn |
| 10 | Data I | 30.46 Mn | 30.46 Mn | - | 10.40 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 10.40 Mn |
| Mar 31, 2026 | 9.39 Mn |
| Dec 31, 2025 | 9.39 Mn |
| Sep 30, 2025 | 9.39 Mn |
| Jun 30, 2025 | 9.37 Mn |
| Mar 31, 2025 | 9.24 Mn |
| Dec 31, 2024 | 9.24 Mn |
| Sep 30, 2024 | 9.24 Mn |
| Jun 30, 2024 | 9.22 Mn |
| Mar 31, 2024 | 9.02 Mn |
| Dec 31, 2023 | 9.02 Mn |
| Sep 30, 2023 | 9.02 Mn |
| Jun 30, 2023 | 9.02 Mn |
| Mar 31, 2023 | 8.82 Mn |
| Dec 31, 2022 | 8.82 Mn |
| Sep 30, 2022 | 8.82 Mn |
| Jun 30, 2022 | 8.81 Mn |
| Mar 31, 2022 | 8.62 Mn |
| Dec 31, 2021 | 8.62 Mn |
| Sep 30, 2021 | 8.62 Mn |
Data I Shares Outstanding (Entity) 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=shares-outstanding-entity&ticker=DAIO&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "shares-outstanding-entity", "ticker": "DAIO", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=shares-outstanding-entity&ticker=DAIO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();