NIKKEI 225
37,779.16 -182.64 (-0.48%) HANG SENG
16,251.84 +2.87 (+0.02%) CRUDE OIL
82.73 +0.04 (+0.05%) GOLD FUTURES
2,383.80 -4.60 (-0.19%) DOW
37,753.31 -45.66 (-0.12%) Bitcoin GBP
49,196.99 -2,026.96 (-3.96%)
NetApp, Inc. (NTA.DE)
| Previous close | 69.35 |
| Open | 69.35 |
| Bid | 0.00 x N/A |
| Ask | 0.00 x N/A |
| Day's range | 69.35 - 69.35 |
| 52-week range | 54.99 - 74.00 |
| Volume | |
| Avg. volume | 9 |
| Market cap | 14.48B |
| Beta (5Y monthly) | 1.27 |
| PE ratio (TTM) | 13.31 |
| EPS (TTM) | 5.21 |
| Earnings date | 30 May 2024 |
| Forward dividend & yield | N/A (N/A) |
| Ex-dividend date | N/A |
| 1y target est | N/A |
Business WireNetApp Partners with Google Cloud to Maximize Flexibility for Cloud Data Storage
SAN JOSE, Calif., April 10, 2024--NetApp® (NASDAQ: NTAP), the intelligent data infrastructure company, today announced an expansion of its partnership with Google Cloud to make it easier for organizations to leverage their data for generative AI (GenAI) and other hybrid cloud workloads. NetApp and Google Cloud are announcing the Flex service level for Google Cloud NetApp Volumes which supports storage volumes of nearly any size. NetApp is also releasing a preview of its GenAI toolkit reference a
Business WireNetApp Wins Google Cloud Technology Partner of the Year Award for Infrastructure - Storage
SAN JOSE, Calif., April 09, 2024--NetApp® (NASDAQ: NTAP), the intelligent data infrastructure company, announced it has received the 2024 Google Cloud Technology Partner of the Year Award in the Infrastructure - Storage category for Google Cloud NetApp Volumes. For the second year in a row, NetApp is recognized for its achievements in the Google Cloud ecosystem, helping joint customers deploy solutions that enable them to easily migrate, deploy, and manage data and workloads in Google Cloud with
Business WireNetApp Empowers Customers to Securely "Talk to Their Data" in Collaboration with NVIDIA
SAN JOSE, Calif., March 18, 2024--NetApp® (NASDAQ: NTAP) today announced it is collaborating with NVIDIA to advance retrieval-augmented generation (RAG) for generative AI applications.
